Stating the Obvious: Writing Assumptions, Limitations, and Delimitations
During the process of writing your thesis or dissertation, you might suddenly realize that your research has inherent flaws. Don’t worry! Virtually all projects contain restrictions to your research. However, being able to recognize and accurately describe these problems is the difference between a true researcher and a grade-school kid with a science-fair project. Concerns with truthful responding, access to participants, and survey instruments are just a few of examples of restrictions on your research. In the following sections, the differences among delimitations, limitations, and assumptions of a dissertation will be clarified.
Delimitations are the definitions you set as the boundaries of your own thesis or dissertation, so delimitations are in your control. Delimitations are set so that your goals do not become impossibly large to complete. Examples of delimitations include objectives, research questions, variables, theoretical objectives that you have adopted, and populations chosen as targets to study. When you are stating your delimitations, clearly inform readers why you chose this course of study. The answer might simply be that you were curious about the topic and/or wanted to improve standards of a professional field by revealing certain findings. In any case, you should clearly list the other options available and the reasons why you did not choose these options immediately after you list your delimitations. You might have avoided these options for reasons of practicality, interest, or relativity to the study at hand. For example, you might have only studied Hispanic mothers because they have the highest rate of obese babies. Delimitations are often strongly related to your theory and research questions. If you were researching whether there are different parenting styles between unmarried Asian, Caucasian, African American, and Hispanic women, then a delimitation of your study would be the inclusion of only participants with those demographics and the exclusion of participants from other demographics such as men, married women, and all other ethnicities of single women (inclusion and exclusion criteria). A further delimitation might be that you only included closed-ended Likert scale responses in the survey, rather than including additional open-ended responses, which might make some people more willing to take and complete your survey. Remember that delimitations are not good or bad. They are simply a detailed description of the scope of interest for your study as it relates to the research design. Don’t forget to describe the philosophical framework you used throughout your study, which also delimits your study.
Limitations of a dissertation are potential weaknesses in your study that are mostly out of your control, given limited funding, choice of research design, statistical model constraints, or other factors. In addition, a limitation is a restriction on your study that cannot be reasonably dismissed and can affect your design and results. Do not worry about limitations because limitations affect virtually all research projects, as well as most things in life. Even when you are going to your favorite restaurant, you are limited by the menu choices. If you went to a restaurant that had a menu that you were craving, you might not receive the service, price, or location that makes you enjoy your favorite restaurant. If you studied participants’ responses to a survey, you might be limited in your abilities to gain the exact type or geographic scope of participants you wanted. The people whom you managed to get to take your survey may not truly be a random sample, which is also a limitation. If you used a common test for data findings, your results are limited by the reliability of the test. If your study was limited to a certain amount of time, your results are affected by the operations of society during that time period (e.g., economy, social trends). It is important for you to remember that limitations of a dissertation are often not something that can be solved by the researcher. Also, remember that whatever limits you also limits other researchers, whether they are the largest medical research companies or consumer habits corporations. Certain kinds of limitations are often associated with the analytical approach you take in your research, too. For example, some qualitative methods like heuristics or phenomenology do not lend themselves well to replicability. Also, most of the commonly used quantitative statistical models can only determine correlation, but not causation.
Assumptions are things that are accepted as true, or at least plausible, by researchers and peers who will read your dissertation or thesis. In other words, any scholar reading your paper will assume that certain aspects of your study is true given your population, statistical test, research design, or other delimitations. For example, if you tell your friend that your favorite restaurant is an Italian place, your friend will assume that you don’t go there for the sushi. It’s assumed that you go there to eat Italian food. Because most assumptions are not discussed in-text, assumptions that are discussed in-text are discussed in the context of the limitations of your study, which is typically in the discussion section. This is important, because both assumptions and limitations affect the inferences you can draw from your study. One of the more common assumptions made in survey research is the assumption of honesty and truthful responses. However, for certain sensitive questions this assumption may be more difficult to accept, in which case it would be described as a limitation of the study. For example, asking people to report their criminal behavior in a survey may not be as reliable as asking people to report their eating habits. It is important to remember that your limitations and assumptions should not contradict one another. For instance, if you state that generalizability is a limitation of your study given that your sample was limited to one city in the United States, then you should not claim generalizability to the United States population as an assumption of your study. Statistical models in quantitative research designs are accompanied with assumptions as well, some more strict than others. These assumptions generally refer to the characteristics of the data, such as distributions, correlational trends, and variable type, just to name a few. Violating these assumptions can lead to drastically invalid results, though this often depends on sample size and other considerations.
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How to Write Assumptions for a Thesis
Kristina barroso, 25 jun 2018.
They say that when you assume, you make a “donkey” out of “you” and “me.” As a result, making assumptions in everyday life does not typically yield positive results. When it comes to research for a thesis or dissertation, though, assumptions are a critical part of the work’s foundation. Assumptions in a thesis are things that your readers will generally accept as either true or plausible, such as the assumption of honest responses from study participants.
Explore this article
- The Importance of Assumptions in a Thesis
- The Importance of a Structured Thesis
- Identifying Assumptions
- Common Assumptions
1 The Importance of Assumptions in a Thesis
One of the first and most important tasks when writing a thesis is to decide what assumptions your readers are likely to have. Research is built on assumptions, which is why they are so important and necessary for your study to be valid and credible. The research problem itself cannot exist without assumptions because those assumptions directly influence what kind of inferences you can reasonably draw from your research.
2 The Importance of a Structured Thesis
A structured thesis is the roadmap for a structured paper. Your thesis statement should clearly present the central argument, and outline the structure that the rest of the paper will follow. You cannot write a thesis statement without knowing which assumptions you are basing the research problem on.
3 Identifying Assumptions
Making incorrect or unreasonable assumptions will likely result in drawing false conclusions based on those flawed assumptions, which is why it is so important to think critically about which assumptions you should or should not be making in your research efforts. A good assumption is one that can be verified or reasonably justified. A bad assumption, on the other hand, is not easily verified or reasonably justified. To ensure that you are making good assumptions, you must do more than simply state what they are. Explain and give examples of why your assumptions are probably true. For example, if you are assuming that participants will provide honest responses to your questions, explain the data collection process and how you will preserve anonymity and confidentiality to maximize truthfulness.
4 Common Assumptions
The most common assumption for a research study is usually the truthfulness with which participants will respond. However, if the questions asked are of a sensitive nature, it is less plausible to assume honesty than in studies where the questions are more mundane. When participant honesty might be compromised, it should be listed as a limitation of the study rather than an assumption. Assumptions and limitations should never contradict each other. Other common assumptions include how representative a given sample is of the population studied, and the similarity of participants’ characteristics within the study.
- 1 Walden University: Addressing Assumptions
About the Author
Kristina Barroso earned a B.A. in Psychology from Florida International University and works full-time as a classroom teacher in a public school. She teaches middle school English to a wide range of students from struggling readers to advanced and gifted populations. In her spare time, she loves writing articles about education for TheClassroom.com, WorkingMother and other education sites.
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Search catalog, critical thinking and academic research: assumptions.
- Point of View
An assumption is an unexamined belief: what we think without realizing we think it. Our inferences (also called conclusions) are often based on assumptions that we haven't thought about critically. A critical thinker, however, is attentive to these assumptions because they are sometimes incorrect or misguided. Just because we assume something is true doesn't mean it is.
Think carefully about your assumptions when finding and analyzing information but also think carefully about the assumptions of others. Whether you're looking at a website or a scholarly article, you should always consider the author's assumptions. Are the author's conclusions based on assumptions that she or he hasn't thought about logically?
- What am I taking for granted?
- Am I assuming something I shouldn't?
- How can I determine whether this assumption is accurate?
- What is this author assuming?
- How can I determine if this author's assumptions are accurate?
Consider the following situations, then respond to these questions:
- Do you agree or disagree with the inference/conclusion? Why or why not?
- What assumption(s) may have led to the inference/conclusion?
- What are some alternative ways of thinking about this situation?
Bill needs six scholarly articles for his paper on the psychological effects of domestic violence. He searches Google for "psychological effects of domestic violence," looks through the first few hits, and finds six sources, including some articles on the websites of legitimate organizations. A few of these articles include bibliographies.
- Bill's Inference/Conclusion: I'm going to stop researching because I have my six sources.
Christie is researching representations of gender in popular music. She decides to search Google and, within a few minutes, locates more sources that she could possibly incorporate into her final paper.
- Christie's Inference/Conclusion: I can just use Google for my research.
Jennifer has decided to write her literary analysis paper on drug use in David Foster Wallace's novel, Infinite Jest (1996). She tries a few Google searches for Infinite Jest, drugs, and drug use, but she has trouble finding scholarly sources. She gives up on Google and moves on to EBSCO Academic Search Premier, one of the databases she heard about in a library instruction class. She runs a search for Infinite Jest and drug use, but she still can't find much.
- Jennifer's Inference/Conclusion: I need to change my topic.
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Tips on making assumptions in a research paper.
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How to make assumptions in a research paper.
In the academic environment, making assumptions is vital as the research statement of the problem when writing a project dissertation . Assumptions in an essay are those statements your audience will take as true or false. Today, we will be looking at making assumptions in research writing and errors to be avoided during this process.
What is assumption?
In academic writing, an assumption is regarded as unexamined belief; that is what we are considering without realizing it. Inarguably all research works conclude based on the assumption that the authors have not critically examined.
The Importance of Assumptions in a thesis
Deciding what assumptions might arise in your readers' minds is one of the primary functions to be carried out when writing a research paper. Without a doubt, assumptions are the foundation of any credible and valid research work. In fact, without assumptions, research problems cannot be found as they determine the conclusions that would be gotten from your research work.
It is essential to point out that the type of assumption will determine the conclusion gotten from the research. For this reason, you should critically consider the kinds of assumptions you make in your research. What then makes a proper assumption? Being able to be verified and justified. To give a reasonable assumption, you must not just state, but explain and cite examples to justify your premise's validity. On the other hand, a wrong assumption is not easily valid and justified. Take, for instance, in case you are assuming that participants will provide honest answers to questions you ask them, explain how the data was gotten, and steps you will take to ensure their identity is protected to guarantee truthfulness.
Assumptions and Hypotheses: Similarities and differences
Many people tend to mix up an assumption with a hypothesis. Although these two concepts share specific characteristics, they are quite different. Below we list two significant similarities and differences between an assumption and thesis.
Similarities between assumption and thesis:
1. Both assumption and hypothesis can be proved and disapproved during the course of the research.
2. Like thesis an assumption must always be affirmative, never a question.
Differences between an assumption and hypothesis:
1. Unlike an assumption, the researcher consciously works towards proving the validity of the hypothesis used for the research.
2.The research work begins based on an assumption, whereas a theory is a goal the study aims to achieve.
Having differentiated between these two concepts, the question now evolves in many writers' minds, what then is a premise in research?
Is Premise and Assumption the same?
A premise is commonly described as the assumption that the arguments depend on ”fly.” In essence, we are saying that an assumption is sometimes referred to as a premise of research work. Let's check out the example below to understand better:
1. All men are mortal;
2. Socrates is a man;
3. Therefore, Socrates is mortal.
From the above example, it is evident that the first two assertions are premises. Why are they assumptions? Because there is no attempt to prove their validity, everyone just accepts them as reality. However, the last statement depends on the first two sentences; if those are untrue, it is also inaccurate and vice versa.
Types of Assumptions
There are two types of Assumptions when writing a research paper: directly stated assumption (explicit) or indirectly stated but implied (Implicitly). So immediately, you pinpoint an assumption in research work, watch out for the two types.
Often, to make an efficient reading, it is necessary to go beyond what has been said, that is, read between the lines.
For example, observe this statement:
Patricia stopped drinking soda The explicit assumption is, “Patricia stopped drinking soda.” The implicit assumption is, “Patricia used to drink soda before.”
Now, see this other example:
Fortunately, Patricia stopped drinking soda
The explicit assumption is, “Patricia stopped drinking soda.” The word “fortunately” indicates that the speaker has a positive opinion of the fact – that is the implicit assumption.
Common Assumptions in Research
Arguably, perhaps the most frequent assumption in any research is around the participants' sincerity when answering the questions being asked. It is important to note that if the questions you ask the respondents are quite sensitive, it is best to assume plausible honesty when compared to answering impersonal questions. If there is element of subjectivity and compromise in the answer being provided, it should be listed as a limitation of the research, not an assumption. Limitations and assumptions of the study should not be in contrast to each other.
Another widespread assumption is the similarity of participants' characteristics within the study. Another common assumption in research is determining the level of representation a sample size is for a population.
Four Ways to Deal with Assumptions
Like we earlier mentioned, regardless of the type of research being carried out, assumptions are vital to its success. Despite the critical role it plays in research writing when you re-evaluate the assumptions you have made, sometimes you feel like they are not accurate enough; hence you want to change the assumption. Below we have highlighted four tips on how to deal with assumptions in research writing.
1. Don't touch them, leave them as they are;
When you see the assumptions, you have made in your research, you may think about leaving them. However, your confidence will be boosted about choosing not to touch them if carefully review them and the options available.
2. Explain them in more detail (make them explicit)
Indeed when you make an assumption, you will likely feel like that is the right thing to do; however, your research work will be more understood if you expound more about the assumption, although you don't need to give examples to back it up.
3. Offer evidence (convert them into supported claims)
We know at this point; you are worried about the fact that we are asking you to provide evidence. Nevertheless, it is something you should consider if you think your audience will probably not agree with one of the assumptions you have made with an example to back it up. So, in this situation, it is ideal for you to turn your assumption into a claim that has proof.
4. Change them (revise the larger claim)
In certain situations, even you are not convinced by the assumption you are presenting to your audience even after several attempts to prove. In this case, the best thing to do is to review the assumption and the statement it serves as a backbone.
Three Common Mistakes about assumptions
When evaluating an assumption, there are inevitable mistakes to be careful of:
Mistake #1: The assumption is terrible because there is no evidence
Many people make a mistake of saying that when an assumption does not have proof, it will fail. However, if you look at the definition of assumption, you will notice that lack of evidence pops out.
Mistake #2: I can't entirely agree because we cannot know if it's true or not
Another common mistake about assumption is that if we cannot know whether it is true or false, we cannot say it is an assumption because there is no room for agreeing or disagreeing. But the reality is that even if we cannot ascertain the assumption, we can make an educated guess and explain the reasons for making the assumption.
Mistake #3: The assumption is reasonable because there is evidence
A lot of people express that when there is proof for an assumption, it is a good one. However, the truth is, when your supposed assumption has evidence, and the author tries to prove it, it is no longer an assumption.
From the above, it is evident that assumption is an integral part of research writing. We believe you can now identify what it is and make assumptions to back up your research.
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- What Is a Case Study? | Definition, Examples & Methods
What Is a Case Study? | Definition, Examples & Methods
Published on May 8, 2019 by Shona McCombes . Revised on June 22, 2023.
A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.
A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .
Table of contents
When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.
A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.
Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.
You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.
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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:
- Provide new or unexpected insights into the subject
- Challenge or complicate existing assumptions and theories
- Propose practical courses of action to resolve a problem
- Open up new directions for future research
TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.
Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.
Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.
However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.
Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.
While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:
- Exemplify a theory by showing how it explains the case under investigation
- Expand on a theory by uncovering new concepts and ideas that need to be incorporated
- Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions
To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.
There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.
Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.
The aim is to gain as thorough an understanding as possible of the case and its context.
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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.
How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .
Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).
In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
- Normal distribution
- Degrees of freedom
- Null hypothesis
- Discourse analysis
- Control groups
- Mixed methods research
- Non-probability sampling
- Quantitative research
- Ecological validity
- Rosenthal effect
- Implicit bias
- Cognitive bias
- Selection bias
- Negativity bias
- Status quo bias
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McCombes, S. (2023, June 22). What Is a Case Study? | Definition, Examples & Methods. Scribbr. Retrieved November 12, 2023, from https://www.scribbr.com/methodology/case-study/
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Definition and Introduction
Case analysis is a problem-based teaching and learning method that involves critically analyzing complex scenarios within an organizational setting for the purpose of placing the student in a “real world” situation and applying reflection and critical thinking skills to contemplate appropriate solutions, decisions, or recommended courses of action. It is considered a more effective teaching technique than in-class role playing or simulation activities. The analytical process is often guided by questions provided by the instructor that ask students to contemplate relationships between the facts and critical incidents described in the case.
Cases generally include both descriptive and statistical elements and rely on students applying abductive reasoning to develop and argue for preferred or best outcomes [i.e., case scenarios rarely have a single correct or perfect answer based on the evidence provided]. Rather than emphasizing theories or concepts, case analysis assignments emphasize building a bridge of relevancy between abstract thinking and practical application and, by so doing, teaches the value of both within a specific area of professional practice.
Given this, the purpose of a case analysis paper is to present a structured and logically organized format for analyzing the case situation. It can be assigned to students individually or as a small group assignment and it may include an in-class presentation component. Case analysis is predominately taught in economics and business-related courses, but it is also a method of teaching and learning found in other applied social sciences disciplines, such as, social work, public relations, education, journalism, and public administration.
Ellet, William. The Case Study Handbook: A Student's Guide . Revised Edition. Boston, MA: Harvard Business School Publishing, 2018; Christoph Rasche and Achim Seisreiner. Guidelines for Business Case Analysis . University of Potsdam; Writing a Case Analysis . Writing Center, Baruch College; Volpe, Guglielmo. "Case Teaching in Economics: History, Practice and Evidence." Cogent Economics and Finance 3 (December 2015). doi:https://doi.org/10.1080/23322039.2015.1120977.
How to Approach Writing a Case Analysis Paper
The organization and structure of a case analysis paper can vary depending on the organizational setting, the situation, and how your professor wants you to approach the assignment. Nevertheless, preparing to write a case analysis paper involves several important steps. As Hawes notes, a case analysis assignment “...is useful in developing the ability to get to the heart of a problem, analyze it thoroughly, and to indicate the appropriate solution as well as how it should be implemented” [p.48]. This statement encapsulates how you should approach preparing to write a case analysis paper.
Before you begin to write your paper, consider the following analytical procedures:
- Review the case to get an overview of the situation . A case can be only a few pages in length, however, it is most often very lengthy and contains a significant amount of detailed background information and statistics, with multilayered descriptions of the scenario, the roles and behaviors of various stakeholder groups, and situational events. Therefore, a quick reading of the case will help you gain an overall sense of the situation and illuminate the types of issues and problems that you will need to address in your paper. If your professor has provided questions intended to help frame your analysis, use them to guide your initial reading of the case.
- Read the case thoroughly . After gaining a general overview of the case, carefully read the content again with the purpose of understanding key circumstances, events, and behaviors among stakeholder groups. Look for information or data that appears contradictory, extraneous, or misleading. At this point, you should be taking notes as you read because this will help you develop a general outline of your paper. The aim is to obtain a complete understanding of the situation so that you can begin contemplating tentative answers to any questions your professor has provided or, if they have not provided, developing answers to your own questions about the case scenario and its connection to the course readings,lectures, and class discussions.
- Determine key stakeholder groups, issues, and events and the relationships they all have to each other . As you analyze the content, pay particular attention to identifying individuals, groups, or organizations described in the case and identify evidence of any problems or issues of concern that impact the situation in a negative way. Other things to look for include identifying any assumptions being made by or about each stakeholder, potential biased explanations or actions, explicit demands or ultimatums , and the underlying concerns that motivate these behaviors among stakeholders. The goal at this stage is to develop a comprehensive understanding of the situational and behavioral dynamics of the case and the explicit and implicit consequences of each of these actions.
- Identify the core problems . The next step in most case analysis assignments is to discern what the core [i.e., most damaging, detrimental, injurious] problems are within the organizational setting and to determine their implications. The purpose at this stage of preparing to write your analysis paper is to distinguish between the symptoms of core problems and the core problems themselves and to decide which of these must be addressed immediately and which problems do not appear critical but may escalate over time. Identify evidence from the case to support your decisions by determining what information or data is essential to addressing the core problems and what information is not relevant or is misleading.
- Explore alternative solutions . As noted, case analysis scenarios rarely have only one correct answer. Therefore, it is important to keep in mind that the process of analyzing the case and diagnosing core problems, while based on evidence, is a subjective process open to various avenues of interpretation. This means that you must consider alternative solutions or courses of action by critically examining strengths and weaknesses, risk factors, and the differences between short and long-term solutions. For each possible solution or course of action, consider the consequences they may have related to their implementation and how these recommendations might lead to new problems. Also, consider thinking about your recommended solutions or courses of action in relation to issues of fairness, equity, and inclusion.
- Decide on a final set of recommendations . The last stage in preparing to write a case analysis paper is to assert an opinion or viewpoint about the recommendations needed to help resolve the core problems as you see them and to make a persuasive argument for supporting this point of view. Prepare a clear rationale for your recommendations based on examining each element of your analysis. Anticipate possible obstacles that could derail their implementation. Consider any counter-arguments that could be made concerning the validity of your recommended actions. Finally, describe a set of criteria and measurable indicators that could be applied to evaluating the effectiveness of your implementation plan.
Use these steps as the framework for writing your paper. Remember that the more detailed you are in taking notes as you critically examine each element of the case, the more information you will have to draw from when you begin to write. This will save you time.
NOTE : If the process of preparing to write a case analysis paper is assigned as a student group project, consider having each member of the group analyze a specific element of the case, including drafting answers to the corresponding questions used by your professor to frame the analysis. This will help make the analytical process more efficient and ensure that the distribution of work is equitable. This can also facilitate who is responsible for drafting each part of the final case analysis paper and, if applicable, the in-class presentation.
Framework for Case Analysis . College of Management. University of Massachusetts; Hawes, Jon M. "Teaching is Not Telling: The Case Method as a Form of Interactive Learning." Journal for Advancement of Marketing Education 5 (Winter 2004): 47-54; Rasche, Christoph and Achim Seisreiner. Guidelines for Business Case Analysis . University of Potsdam; Writing a Case Study Analysis . University of Arizona Global Campus Writing Center; Van Ness, Raymond K. A Guide to Case Analysis . School of Business. State University of New York, Albany; Writing a Case Analysis . Business School, University of New South Wales.
Structure and Writing Style
A case analysis paper should be detailed, concise, persuasive, clearly written, and professional in tone and in the use of language . As with other forms of college-level academic writing, declarative statements that convey information, provide a fact, or offer an explanation or any recommended courses of action should be based on evidence. If allowed by your professor, any external sources used to support your analysis, such as course readings, should be properly cited under a list of references. The organization and structure of case analysis papers can vary depending on your professor’s preferred format, but its structure generally follows the steps used for analyzing the case.
The introduction should provide a succinct but thorough descriptive overview of the main facts, issues, and core problems of the case . The introduction should also include a brief summary of the most relevant details about the situation and organizational setting. This includes defining the theoretical framework or conceptual model on which any questions were used to frame your analysis.
Following the rules of most college-level research papers, the introduction should then inform the reader how the paper will be organized. This includes describing the major sections of the paper and the order in which they will be presented. Unless you are told to do so by your professor, you do not need to preview your final recommendations in the introduction. U nlike most college-level research papers , the introduction does not include a statement about the significance of your findings because a case analysis assignment does not involve contributing new knowledge about a research problem.
Background analysis can vary depending on any guiding questions provided by your professor and the underlying concept or theory that the case is based upon. In general, however, this section of your paper should focus on:
- Providing an overarching analysis of problems identified from the case scenario, including identifying events that stakeholders find challenging or troublesome,
- Identifying assumptions made by each stakeholder and any apparent biases they may exhibit,
- Describing any demands or claims made by or forced upon key stakeholders, and
- Highlighting any issues of concern or complaints expressed by stakeholders in response to those demands or claims.
These aspects of the case are often in the form of behavioral responses expressed by individuals or groups within the organizational setting. However, note that problems in a case situation can also be reflected in data [or the lack thereof] and in the decision-making, operational, cultural, or institutional structure of the organization. Additionally, demands or claims can be either internal and external to the organization [e.g., a case analysis involving a president considering arms sales to Saudi Arabia could include managing internal demands from White House advisors as well as demands from members of Congress].
Throughout this section, present all relevant evidence from the case that supports your analysis. Do not simply claim there is a problem, an assumption, a demand, or a concern; tell the reader what part of the case informed how you identified these background elements.
Identification of Problems
In most case analysis assignments, there are problems, and then there are problems . Each problem can reflect a multitude of underlying symptoms that are detrimental to the interests of the organization. The purpose of identifying problems is to teach students how to differentiate between problems that vary in severity, impact, and relative importance. Given this, problems can be described in three general forms: those that must be addressed immediately, those that should be addressed but the impact is not severe, and those that do not require immediate attention and can be set aside for the time being.
All of the problems you identify from the case should be identified in this section of your paper, with a description based on evidence explaining the problem variances. If the assignment asks you to conduct research to further support your assessment of the problems, include this in your explanation. Remember to cite those sources in a list of references. Use specific evidence from the case and apply appropriate concepts, theories, and models discussed in class or in relevant course readings to highlight and explain the key problems [or problem] that you believe must be solved immediately and describe the underlying symptoms and why they are so critical.
This section is where you provide specific, realistic, and evidence-based solutions to the problems you have identified and make recommendations about how to alleviate the underlying symptomatic conditions impacting the organizational setting. For each solution, you must explain why it was chosen and provide clear evidence to support your reasoning. This can include, for example, course readings and class discussions as well as research resources, such as, books, journal articles, research reports, or government documents. In some cases, your professor may encourage you to include personal, anecdotal experiences as evidence to support why you chose a particular solution or set of solutions. Using anecdotal evidence helps promote reflective thinking about the process of determining what qualifies as a core problem and relevant solution .
Throughout this part of the paper, keep in mind the entire array of problems that must be addressed and describe in detail the solutions that might be implemented to resolve these problems.
Recommended Courses of Action
In some case analysis assignments, your professor may ask you to combine the alternative solutions section with your recommended courses of action. However, it is important to know the difference between the two. A solution refers to the answer to a problem. A course of action refers to a procedure or deliberate sequence of activities adopted to proactively confront a situation, often in the context of accomplishing a goal. In this context, proposed courses of action are based on your analysis of alternative solutions. Your description and justification for pursuing each course of action should represent the overall plan for implementing your recommendations.
For each course of action, you need to explain the rationale for your recommendation in a way that confronts challenges, explains risks, and anticipates any counter-arguments from stakeholders. Do this by considering the strengths and weaknesses of each course of action framed in relation to how the action is expected to resolve the core problems presented, the possible ways the action may affect remaining problems, and how the recommended action will be perceived by each stakeholder.
In addition, you should describe the criteria needed to measure how well the implementation of these actions is working and explain which individuals or groups are responsible for ensuring your recommendations are successful. In addition, always consider the law of unintended consequences. Outline difficulties that may arise in implementing each course of action and describe how implementing the proposed courses of action [either individually or collectively] may lead to new problems [both large and small].
Throughout this section, you must consider the costs and benefits of recommending your courses of action in relation to uncertainties or missing information and the negative consequences of success.
The conclusion should be brief and introspective. Unlike a research paper, the conclusion in a case analysis paper does not include a summary of key findings and their significance, a statement about how the study contributed to existing knowledge, or indicate opportunities for future research.
Begin by synthesizing the core problems presented in the case and the relevance of your recommended solutions. This can include an explanation of what you have learned about the case in the context of your answers to the questions provided by your professor. The conclusion is also where you link what you learned from analyzing the case with the course readings or class discussions. This can further demonstrate your understanding of the relationships between the practical case situation and the theoretical and abstract content of assigned readings and other course content.
Problems to Avoid
The literature on case analysis assignments often includes examples of difficulties students have with applying methods of critical analysis and effectively reporting the results of their assessment of the situation. A common reason cited by scholars is that the application of this type of teaching and learning method is limited to applied fields of social and behavioral sciences and, as a result, writing a case analysis paper can be unfamiliar to most students entering college.
After you have drafted your paper, proofread the narrative flow and revise any of these common errors:
- Unnecessary detail in the background section . The background section should highlight the essential elements of the case based on your analysis. Focus on summarizing the facts and highlighting the key factors that become relevant in the other sections of the paper by eliminating any unnecessary information.
- Analysis relies too much on opinion . Your analysis is interpretive, but the narrative must be connected clearly to evidence from the case and any models and theories discussed in class or in course readings. Any positions or arguments you make should be supported by evidence.
- Analysis does not focus on the most important elements of the case . Your paper should provide a thorough overview of the case. However, the analysis should focus on providing evidence about what you identify are the key events, stakeholders, issues, and problems. Emphasize what you identify as the most critical aspects of the case to be developed throughout your analysis. Be thorough but succinct.
- Writing is too descriptive . A paper with too much descriptive information detracts from your analysis of the complexities of the case situation. Questions about what happened, where, when, and by whom should only be included as essential information leading to your examination of questions related to why, how, and for what purpose.
- Inadequate definition of a core problem and associated symptoms . A common error found in case analysis papers is recommending a solution or course of action without adequately defining or demonstrating that you understand the problem. Make sure you have clearly described the problem and its impact and scope within the organizational setting. Ensure that you have adequately described the root causes w hen describing the symptoms of the problem.
- Recommendations lack specificity . Identify any use of vague statements and indeterminate terminology, such as, “A particular experience” or “a large increase to the budget.” These statements cannot be measured and, as a result, there is no way to evaluate their successful implementation. Provide specific data and use direct language in describing recommended actions.
- Unrealistic, exaggerated, or unattainable recommendations . Review your recommendations to ensure that they are based on the situational facts of the case. Your recommended solutions and courses of action must be based on realistic assumptions and fit within the constraints of the situation. Also note that the case scenario has already happened, therefore, any speculation or arguments about what could have occurred if the circumstances were different should be revised or eliminated.
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Ca se Study and Case Analysis Are Not the Same!
Confusion often exists between what it means to write a paper that uses a case study research design and writing a paper that analyzes a case; they are two different types of approaches to learning in the social and behavioral sciences. Professors as well as educational researchers contribute to this confusion because they often use the term "case study" when describing the subject of analysis for a case analysis paper. But you are not studying a case for the purpose of generating a comprehensive, multi-faceted understanding of a research problem. R ather, you are critically analyzing a specific scenario to argue logically for recommended solutions and courses of action that lead to optimal outcomes applicable to professional practice.
To avoid any confusion, here are twelve characteristics that delineate the differences between writing a paper using the case study research method and writing a case analysis paper:
- Case study is a method of in-depth research and rigorous inquiry ; case analysis is a reliable method of teaching and learning . A case study is a modality of research that investigates a phenomenon for the purpose of creating new knowledge, solving a problem, or testing a hypothesis using empirical evidence derived from the case being studied. Often, the results are used to generalize about a larger population or within a wider context. The writing adheres to the traditional standards of a scholarly research study. A case analysis is a pedagogical tool used to teach students how to reflect and think critically about a practical, real-life problem in an organizational setting.
- The researcher is responsible for identifying the case to study; a case analysis is assigned by your professor . As the researcher, you choose the case study to investigate in support of obtaining new knowledge and understanding about the research problem. The case in a case analysis assignment is almost always provided, and sometimes written, by your professor and either given to every student in class to analyze individually or to a small group of students, or students select a case to analyze from a predetermined list.
- A case study is indeterminate and boundless; a case analysis is predetermined and confined . A case study can be almost anything [see item 9 below] as long as it relates directly to examining the research problem. This relationship is the only limit to what a researcher can choose as the subject of their case study. The content of a case analysis is determined by your professor and its parameters are well-defined and limited to elucidating insights of practical value applied to practice.
- Case study is fact-based and describes actual events or situations; case analysis can be entirely fictional or adapted from an actual situation . The entire content of a case study must be grounded in reality to be a valid subject of investigation in an empirical research study. A case analysis only needs to set the stage for critically examining a situation in practice and, therefore, can be entirely fictional or adapted, all or in-part, from an actual situation.
- Research using a case study method must adhere to principles of intellectual honesty and academic integrity; a case analysis scenario can include misleading or false information . A case study paper must report research objectively and factually to ensure that any findings are understood to be logically correct and trustworthy. A case analysis scenario may include misleading or false information intended to deliberately distract from the central issues of the case. The purpose is to teach students how to sort through conflicting or useless information in order to come up with the preferred solution. Any use of misleading or false information in academic research is considered unethical.
- Case study is linked to a research problem; case analysis is linked to a practical situation or scenario . In the social sciences, the subject of an investigation is most often framed as a problem that must be researched in order to generate new knowledge leading to a solution. Case analysis narratives are grounded in real life scenarios for the purpose of examining the realities of decision-making behavior and processes within organizational settings. A case analysis assignments include a problem or set of problems to be analyzed. However, the goal is centered around the act of identifying and evaluating courses of action leading to best possible outcomes.
- The purpose of a case study is to create new knowledge through research; the purpose of a case analysis is to teach new understanding . Case studies are a choice of methodological design intended to create new knowledge about resolving a research problem. A case analysis is a mode of teaching and learning intended to create new understanding and an awareness of uncertainty applied to practice through acts of critical thinking and reflection.
- A case study seeks to identify the best possible solution to a research problem; case analysis can have an indeterminate set of solutions or outcomes . Your role in studying a case is to discover the most logical, evidence-based ways to address a research problem. A case analysis assignment rarely has a single correct answer because one of the goals is to force students to confront the real life dynamics of uncertainly, ambiguity, and missing or conflicting information within professional practice. Under these conditions, a perfect outcome or solution almost never exists.
- Case study is unbounded and relies on gathering external information; case analysis is a self-contained subject of analysis . The scope of a case study chosen as a method of research is bounded. However, the researcher is free to gather whatever information and data is necessary to investigate its relevance to understanding the research problem. For a case analysis assignment, your professor will often ask you to examine solutions or recommended courses of action based solely on facts and information from the case.
- Case study can be a person, place, object, issue, event, condition, or phenomenon; a case analysis is a carefully constructed synopsis of events, situations, and behaviors . The research problem dictates the type of case being studied and, therefore, the design can encompass almost anything tangible as long as it fulfills the objective of generating new knowledge and understanding. A case analysis is in the form of a narrative containing descriptions of facts, situations, processes, rules, and behaviors within a particular setting and under a specific set of circumstances.
- Case study can represent an open-ended subject of inquiry; a case analysis is a narrative about something that has happened in the past . A case study is not restricted by time and can encompass an event or issue with no temporal limit or end. For example, the current war in Ukraine can be used as a case study of how medical personnel help civilians during a large military conflict, even though circumstances around this event are still evolving. A case analysis can be used to elicit critical thinking about current or future situations in practice, but the case itself is a narrative about something finite and that has taken place in the past.
- Multiple case studies can be used in a research study; case analysis involves examining a single scenario . Case study research can use two or more cases to examine a problem, often for the purpose of conducting a comparative investigation intended to discover hidden relationships, document emerging trends, or determine variations among different examples. A case analysis assignment typically describes a stand-alone, self-contained situation and any comparisons among cases are conducted during in-class discussions and/or student presentations.
The Case Analysis . Fred Meijer Center for Writing and Michigan Authors. Grand Valley State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Ramsey, V. J. and L. D. Dodge. "Case Analysis: A Structured Approach." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 27-29; Yin, Robert K. Case Study Research and Applications: Design and Methods . 6th edition. Thousand Oaks, CA: Sage, 2017; Crowe, Sarah et al. “The Case Study Approach.” BMC Medical Research Methodology 11 (2011): doi: 10.1186/1471-2288-11-100; Yin, Robert K. Case Study Research: Design and Methods . 4th edition. Thousand Oaks, CA: Sage Publishing; 1994.
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Working with Assumptions in International Development Program Evaluation pp 97–114 Cite as
Why Are Assumptions Important?
- Apollo M. Nkwake 2
- First Online: 28 November 2019
Assumptions are the foci for any theory and thus any paradigm. It is important to make assumptions explicit and to make a sufficient number of assumptions to describe the phenomenon at hand. Explication of assumptions is even more crucial in research methods used to test the theories. As Mitroff and Bonoma (Evaluation quarterly 2:235–60, 1978, p. 235) put it, “… the power of an experiment is only as strong as the clarity of the basic assumptions which underlie it. Such assumptions not only underlie laboratory experimentation but social evaluation research as well.” Assumptions can be rated on a scale of articulation from tacit to explicit.
- Importance of assumptions
- Evidence generation
- Methodology selection
- Ontological assumptions
- Epistemological assumptions
- Foci of paradigms
- Assumptions in theory
- Explicating assumptions
- Scale of assumptions articulation
Apparently, assumption is believed to provide an easy or lazy person’s way out of what seems to be—at least at first glance—a perplexing situation … At least, one is not justified in going ahead and making some assumption which moderately expressed is wholly an arbitrary one … Accuracy of interpretation never can be supplanted by assumption. I assume one thing, you assume something else, and the other fellows each assume something different from each of the others. Grant the acceptance of assumption, and then any one of a hundred different solutions is correct. Could anything be more ridiculous? – Bennett ( 1933 )
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Nkwake, A.M. (2020). Why Are Assumptions Important?. In: Working with Assumptions in International Development Program Evaluation. Springer, Cham. https://doi.org/10.1007/978-3-030-33004-0_7
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Evans D, Coad J, Cottrell K, et al. Public involvement in research: assessing impact through a realist evaluation. Southampton (UK): NIHR Journals Library; 2014 Oct. (Health Services and Delivery Research, No. 2.36.)
Public involvement in research: assessing impact through a realist evaluation.
Appendix 4 assumptions made for case study projections from information gained during data collection.
- Case study 1
Public involvement activity included representation on various study committees, for example a stakeholder reference group, as well as a stakeholder event due to be delivered towards the end of the project.
- Case study 2
The funded grant application did not include a separate costing for public involvement, but a stakeholder time and travel budget of £27,000 was included to cover all costs for both public and stakeholder participation in this research. Of this, £7000 was allocated for public involvement activity over a 3-year study period: £2000 per year, plus £1000 contingency.
- Case study 3
Public involvement was not a separate costing item in the funded grant proposal, so any costs associated with involvement would have been taken from the general project budget.
- Case study 4
Public involvement-related activity was not costed separately in the grant application, so any costs associated with involvement were taken out of the general project budget. During the interview, the researcher estimated that there would be approximately 1 month of her time devoted to public involvement activity over the 5-year research programme. We were able to put a value on this person’s time using an hourly wage rate in order to calculate the amount of input used. The total research project costs associated with facilitating public involvement in research were £3616; this did not include reimbursement of travel costs/refreshment costs and so forth.
- Case study 5
£22,200, around 5% of the total grant, was budgeted for PPI. A devolved model of public involvement was applied, whereby the lead organisation had a service level agreement with four service user organisations across England. We have collected resource data from one of the service user organisations, £3000, and have made the assumption that the other three organisations will have similar resource inputs: £12,000 in total. A further service level agreement has been written between the lead organisation and the service user organisation up until the end of the project. Two further national advisory meetings are planned = £4464. In addition, there have been two previous national advisory meetings prior to November 2011 at a cost of £4464. Total project costs = £41,391.
- Case study 6
The total grant awarded was nearly $180,000 over a 2-year study period. Public involvement-related activity was not separately included, but a travel budget of nearly $33,000 and living expenses of $6900 were included for both project researchers and patient experts to attend international project meetings. We can estimate that of this amount approximately $11,900 was for travel and $3500 for living expenses of four or five patient experts to attend project meetings in Europe and North America. Given this reasoning and assumptions the public involvement budget is approximately $15,345 (around 8.5% of the total grant).
- Case study 7
The total value of the award is approximately £248,000, with a budget for public involvement of £2970 (around 1.2% of the total grant) for patient partner travel and advisory group meetings including provision for light lunches and study participants‘ travel expenses.
- Case study 8
This is an ongoing programme grant, which primarily maintains a cohort of individuals and their data. These individuals form a public involvement panel that can be accessed by researchers as required.
Included under terms of UK Non-commercial Government License .
- Cite this Page Evans D, Coad J, Cottrell K, et al. Public involvement in research: assessing impact through a realist evaluation. Southampton (UK): NIHR Journals Library; 2014 Oct. (Health Services and Delivery Research, No. 2.36.) Appendix 4, Assumptions made for case study projections from information gained during data collection.
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Case Study: Using the 5 Whys to Validate Assumptions
Published: February 24, 2014 by Jerry Shih
The effectiveness of any process improvement tool depends on the process improvement practitioners’ assessment of the situation, choice of the simplest tool and the creative use of the tool. This article provides an example of how a simple tool, the 5 Whys , was used to unearth an assumption embedded in a business process. Once the assumption was revealed and tested with data, impressive results ensued.
The 5 Whys is an iterative question-asking technique to identify the root cause underlying a particular symptom. Consider a situation in which a child throws a tantrum and refuses to go to school. Table 1 shows the application of the 5 Whys to this situation.
The deeper the questions of “why” go, the more likely that the root cause of a situation will be revealed. In this example, the parent needs to address the situation – the child’s temperature needs to be brought down. The root cause, however, is how a parent manages themselves during the power struggle. In this case, the way the parent was raised is not something that the parent can change. But awareness of the underlying assumption means it can be questioned or changed.
Case Study: Large West Coast Marina
Attendants at a large West Coast marina had been complaining about the time-consuming nature of the process for collecting fees for short-term moorage (i.e., parking for boats) – it took time away from other activities that were potentially more profitable for the marina. Through the marina’s strategic planning, this process was targeted for improvement.
Originally the daily process for collecting short-term moorage fees took 12 hours and included four major steps:
- Boaters write the boat name, number and moorage space number on a marina-provided envelope, enclose the fees, and drop it in a deposit box.
- A moorage attendant picks up all of the envelopes twice a day. The counter attendant processes the contents and inputs all envelope data into the payment system. This step takes approximately two hours per day.
- Twice a day, an attendant walks the docks and writes down all of the boat names, numbers and moorage space numbers on a form and takes the form to the counter attendant for input into the payment system. This step takes approximately 10 hours per day.
- Invoices are automatically sent to boaters for collection discrepancies in moorage usage fees on a monthly basis.
The moorage attendants informed marina management that there was a lot of data entry duplication – the same data is recorded on paper and then entered into a payment system . They learned that other marinas equipped their attendants with a handheld device for inputting all boat information, which is then uploaded by the office attendant into the payment system. Marina management budgeted $100,000 for the implementation of this automated system and engaged a third-party company to 1) document the as-is and to-be processes, 2) write a business case to justify the investment and 3) produce a business-requirements document for the implementation.
When the consulting company began to document the current state, the activity of sending invoices to boaters (Step 4) for short-term moorage stood out. This type of activity is not normally seen in the similar situation of short-term parking for cars. The consultant suggested that exploring this approach to invoicing would be worthwhile before moving forward with the technological solution. The client agreed; the consultants partnered with the attendants to learn more about this process.
Why Send Invoices
The project team used the 5 Whys to discover why the activity of sending invoices to boaters was performed in the first place. The situation: Monthly invoices are automatically sent to boaters for collection of any discrepancies in moorage usage fees.
Validating the Assumption
The underlying assumption is that boaters cannot be trusted and that given the opportunity, the short-term moorage users will either purposely not pay or underpay their daily moorage fees. Many of the activities within the fee collection process were established to ensure that all of the fees were collected. The consultants asked the operational team to test this assumption with data and created a standard form for them to use. The marina team went back through its records for the past two years and discovered that 99.5 percent of moorage customers voluntarily paid their moorage fees; the average underpaid amount was 54 cents. The team also learned that customers often overpaid because they did not have exact change. The team concluded that it was not cost effective to spend $300 a day to chase an average of $2.60 a day.
Before and After Process
For a $5,000 investment of consulting and staff time, the return on investment was outstanding.
- The marina redirected 10 hours per day to customer valued activities that were previously performed with staff overtime.
- The marina withdrew the decision to make a $100,000 capital investment on a technological solution.
- The marina eliminated the mailing of monthly invoices.
- These simple changes led to a total hard savings of $200,000 in the first year and $100,000 in the following years. The soft saving was a much happier moorage staff.
Will These Results Last?
A question surfaced during the improvement process: Two years of data showed that 99.5 percent of moorage customers voluntarily paid their moorage fee and the average underpaid situation was 54 cents – but how can the marina be certain that this situation will continue? That the results will be sustained ? The consulting company facilitated a solution in which the marina established a monthly audit to verify that the numbers continued to meet expectations. Attendants will randomly pick 20 boats and confirm whether those 20 boats made their fee payments. If there is an increase in the number of “no payments” or “underpayments,” then a reassessment will be undertaken.
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How science REALLY works...
- Understanding Science 101
- All scientific tests involve making assumptions.
- These assumptions can be independently tested, increasing our confidence in our test results.
Much as we might like to avoid it, all scientific tests involve making assumptions — many of them justified. For example, imagine a very simple test of the hypothesis that substance A stops bacterial growth. Some Petri dishes are spread with a mixture of substance A and bacterial growth medium, and others are spread with a mixture of inert substance B and bacterial growth medium. Bacteria are spread on all the Petri dishes, and one day later, the plates are examined to see which fostered the growth of bacterial colonies and which did not. This test is straightforward, but still relies on many assumptions: we assume that the bacteria can grow on the growth medium, we assume that substance B does not affect bacterial growth, we assume that one day is long enough for colonies to grow, and we assume that the color pen we use to mark the outside of the dishes is not influencing bacterial growth.
Technically, these are all assumptions, but they are perfectly reasonable ones that can be tested. The scientist performing the experiment described above would justify many of her assumptions by performing additional tests in parallel with the experimental ones. For example, she would separately test whether substance B affects bacterial growth to check that it was indeed inert as she’d assumed. Other assumptions are justified by past tests performed by other scientists. For instance, the question of whether or not bacteria can grow on the growth medium would have been studied by many previous researchers. And some assumptions might remain untested simply because all of our knowledge about the field suggests that the assumption is a safe one (e.g., we know of no reason why bacteria should multiply faster when their dishes are marked with a red, rather than a green, pen). All tests involve assumptions, but most of these are assumptions that can and have been verified separately.
Nevertheless, when evaluating an idea in light of test results, it’s important to keep in mind the test’s assumptions and how well-supported they are. If an expectation generated by an idea is not borne out in a test, it might be because the idea is wrong and should be rejected, or it might be that the idea is right, but an assumption of the test has been violated. And if the test results end up lending support to the idea, it might be because the idea is correct and should be accepted , or it might be because a violated assumption has produced a false positive result.
- Science in action
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Very complex hypotheses — for example, regarding the Earth’s atmosphere — sometimes rely on many sub-hypotheses, or assumptions. To see an example of how changes in these assumptions can affect the over-arching hypothesis, check out the story Ozone depletion: Uncovering the hidden hazard of hairspray .
- All the assumptions that are part of a particular test are also, in a sense, hypotheses — ideas about how something works that could be correct or incorrect. How does science investigate any single hypothesis if they always get bundled together in our tests? To find out, visit Bundle up your hypotheses .
- All of science is based on a few fundamental assumptions that transcend any individual experiment or study. To learn what these are, visit Basic assumptions of science .
Competing ideas: Other considerations
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How to Create Assumptions
How to create the assumptions for startup financial models
If you're like 90% of the entrepreneurs I talk to, your first question when you start building your financial model is "what do I input as my assumptions?" Building forward-looking projections for uncertain businesses is by nature difficult: how do we predict how people will adopt or use something that doesn't exist? And without good assumptions, isn't my model useless?
There's a couple ways to address this:
- Research: Use the past performance of other companies as data points for your assumptions. Thankfully, there is more and more data coming to open circles that you can use to benchmark your assumptions: every startup post-mortem has data points, many Quora posts offer data points for comparison, countless blog posts discuss what to expect for a range of rates or metrics. Gather as much data as you can, understand how someone else's experience can inform yours based on difference in product, approach, stage, etc. (and how your experience will likely differ), and use them to benchmark your assumptions.
- Historical metrics: If you have past performance data, that adds potential data points to your forward-looking assumptions. It doesn't provide the exact answers, since future performance may not look like the past, but it's one data point to help you ground your assumptions. And it helps you understand what metrics in your business you'd need to change to make a big breakthrough in performance.
- Make range estimates, not point estimates: Instead of agonizing over whether your conversion rate will be 2% or 5%, focus on the possible range or conversion rates and evaluate the results based upon the range of estimates, not the point estimate of 2% or 5%. Creating a range helps you focus your thinking how the inputs influence the outputs, rather than focusing narrowly on justifying the inputs.
How do you use assumptions in a model? #
- Use assumptions as variables: Don't hard-code assumptions into formulas. Instead, create your assumptions so that you can easily change an assumption in one place and all formulas and outputs will recalcuate automatically.
- Label assumptions clearly: Use descriptive labels so you can understand what assumptions mean. Add notes to your assumptions so you can clearly explain what they mean.
- Organize your assumptions together: There are multiple ways to approach this, but a general best practice is to organize your assumptions together on a single sheet, so that it's easy to see all the assumptions at the same time in a "control center" for your model.
- Show your work. Part of the reason it's best practice to structure assumptions as variables is so that it's easy to change assumptions later with a minimal amount of effort, but another reason is that it helps expose your thinking and structure. This carries itself into the rest of your model: show how your calculations work by breaking your thinking into multiple lines, rather than condense calculations into a single line. In the example below, you can see two approaches to a basic user and revenue buildup: I've laid out a couple assumptions and then calculated users and revenue in two ways. One exposes a lot more information that can lead to better intermediate decision-making, one condenses the calculations and is harder to see the independent impact of changing the assumptions. Note: you'll notice the calculated user and revenue numbers are different, that's because I rounded up the user numbers more granularly for option 2, and that led to a slightly different ending result.
In the Standard Financial Model (screenshot below), I organize all of the assumptions for the model on a single sheet, grouping them together by section, label and provide details about each assumption, and use a formatting convention (blue text color) to denote all assumptions. My goal is to easily signify where the assumptions are in the model and what they mean, so that anyone can figure out what's going on as quickly as possible. 
I also usually create a separate "Key Metrics" section where summarize key inputs and outputs in the model. I'll pull out key metrics that are calculated in other places in the models and report them in the Key Metrics section so that it's easy to see them in one place. I will also create a Key Inputs section next to the Key Metrics to pull out important assumptions from the Assumptions sheet and place them next to the metrics, so that I can easily change key inputs and see how the metrics change, instantly.
In the Venture Fund Model (screenshot below) I have an assumptions page with all the assumptions in the model, but I've pulled out a couple key assumptions - fund size, check size, type of deal, etc. - and placed them next to the performance metrics so I can easily see how the inputs impact the outputs. That helps me understand how key assumptions impact the model and helps me quickly scan to see if a model is performing like I expect it to.
Structurally creating assumptions in a model is easy, grounding and justifying assumptions is much harder. Start with a good, clean struture, but don't get hung up on grounding your assumptions perfectly when you start building a model. As you build your model you'll change what assumptions you need, add new assumptions, and find out new data to use. Just focus on continuing to build and understand, and come back to your assumptions once you have the outputs of the model ready to evaluate.
You'll notice that I don't necessarily show my work in all places in this model. It's partly because I've tried to make the models a little lighter visually and use less lines for calculations, but it's also because many of the formulas use a mix of index and range functions for a lot of calculations, and it's cleaner for users to see the final result rather than the many intermediate calcs involved in those types of formulas. ↩︎
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What are the assumptions of case study?
Table of Contents
- 1 What are the assumptions of case study?
- 2 How do you write assumptions in a case study?
- 3 What are the objectives of case study?
- 4 What is case study as a method of data collection?
- 5 What are the objectives of case study method?
- 6 What is the goal of the case study?
- 7 What are assumptions in research paper?
Assumptions that case study research is largely interpretivist, inductive and qualitative, are unfounded. The choice of research tradition drives the whole of the research strategy, including phrasing of research objectives, data collection and data analysis and detail.
How do you write assumptions in a case study?
Tips on Making Assumptions in a Research Paper
- Don’t touch them, leave them as they are;
- Explain them in more detail (make them explicit)
- Offer evidence (convert them into supported claims)
- Change them (revise the larger claim)
What are the characteristics of case study method?
Characteristics of Case Study
- The number of unit to be studied is small.
- It studies a social unit deeply and thoroughly.
- It is qualitative as well as quantitative.
- It covers sufficient wide cycle of time.
- It has continuity in nature.
What is the method in a case study?
The case study method is a learning technique in which the student is faced a particular problem, the case. The case study facilitates the exploration of a real issue within a defined context, using a variety of data sources (Baxter et al., 2008).
What are the objectives of case study?
The general purpose of a case study is to: → describe an individual situation (case), e.g. a person, business, organisation, or institution, in detail; → identify the key issues of the case (your assignment question should tell you what to focus on); → analyse the case using relevant theoretical concepts from your unit …
What is case study as a method of data collection?
A case study in psychology is a descriptive research approach used to obtain in-depth information about a person, group, or phenomenon. Case studies use techniques such as personal interviews, direct observation, psychometric tests, and archival records to gather information.
What are the advantages of case study method?
List of the Advantages of the Case Study Method
- It turns client observations into useable data.
- It turns opinion into fact.
- It is relevant to all parties involved.
- It uses a number of different research methodologies.
- It can be done remotely.
- It is inexpensive.
- It is very accessible to readers.
What is case study method with example?
Prospective case study methods are those in which an individual or group of people is observed in order to determine outcomes. For example, a group of individuals might be watched over an extended period of time to observe the progression of a particular disease.
What are the objectives of case study method?
What is the goal of the case study.
The purpose of an explanatory case study is to better show the data and description of a casual investigation. Collective case study’s purpose is to show the detail of how a group of individuals in a manner that shows all the data concisely. The purpose of a descriptive case study is to be able to compare the new gatherings to the preexisting theory.
What are the limitations of case study?
What are assumptions in a research proposal?
What are assumptions in research paper?
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How to Write Assumptions for a Thesis
By William G. It is important to know just what an assumption is when it is applied to research in general and your dissertation in particular. In the Dictionary of Statistics and Methodology, W.Paul Vogt defines an assumption as "(a) A statement that is presumed to be true, often only temporarily or for a specific purpose, such as building a theory; (b) The conditions under which statistical techniques yield valid results." For assumptions -examples: If you are writing a qualitative dissertation, such as case study, ethnography, grounded theory, narrative research, or phenomenology, here are some common assumptions to consider: 1. The participants will answer the interview questions in an honest and candid manner. 2. The inclusion criteria of the sample are appropriate and therefore, assures that the participants have all experienced the same or similar phenomenon of the study. 3. Participants have a sincere interest in participating in your research and do not any other motives,...
JASH MATHEW , MAURICE MUKINGINYI WEKESA
The purpose of the study was to analyze the determinants of effective fraud management in domestic tier one commercial banks in Trans Nzoia County. The analysis was focused on the domestic tier one commercial banks in the County as the population of the study. The study was guided by the following objectives; to analyze the effect of the independence of the internal audit personnel, the competence of the internal audit personnel, the presence of the internal audit charter and the management support as determinants of effective fraud management in the d0mestic tier one commercial banks. The study was guided by the agency theory, the fraud management lifecycle/theory and the communication theory. A correlation research design was adopted in which an in-depth study of the determinants of effective fraud management was carried out from the target population of the senior management staff and the internal audit personnel in the domestic tier one commercial banks in the County. The survey targeted departmental heads in the banks by employing census method. The source of the required data was through the questionnaires, covering both qualitative and quantitative data, administered to the target population by the researcher. The questionnaire was designed for data collection and eventual analysis by both the regression tools and ANOVA using the Statistical Package for Social Sciences (SPSS) version 22. A multiple correlation coefficient and regression analysis together with the ANOVA test were carried out to establish the relationship between the independent variables and dependent variable. The findings revealed that the regression effect is statistically significant and indicated an accomplished prediction of the dependent variable, better than if done through chance through the F calculated (F =12.2896) which was greater than 5% level of significance that showed the overall model was significant where the Internal Audit Independence explained 11% of EFM, Competence of Internal Auditor Personnel 46% of EFM, Presence of Internal Audit Charter 12% of EFM, and Management Support explained 16% of EFM within the domestic tier one commercial banks. However, Competence of Internal Audit Personnel was the most significant predictor (determinant) of EFM at 46% with (β=0.086). The results are expected to contribute to the existing body of knowledge for the crucial role of internal audit function in the banking industry as well as forming a basis for scholars who may want to study issues related to effective fraud management in the banking sector. They are further expected to help in revealing key issues that help improve the success of internal audit section within commercial banks, and also help unearth the fundamental issues related to Internal Audit management in the banking sector.
The main objective of the study was to determine the influence of organizational restructuring on employee job satisfaction in selected commercial banks in Kenya. The study was guided by the following specific objectives; to establish the influence of downsizing, centralization, downscoping and business process reengineering on employee job satisfaction in selected commercial banks in Kenya. The study used stratified random sampling to select the sample 230 of employees at Kenya Commercial Bank and National Bank headquarters. Primary data was collected by using questionnaires. Data was analyzed using Statistical Package for Social Sciences (SPSS). Correlation analysis was used to establish whether there is a relationship between the dependent and independent variable. Multiple regression analysis was used to show the weight of the relationship between the independent and dependent variables. The study established that downsizing had a significant negative relationship with employee job satisfaction in selected commercial banks in Kenya; centralization had a significant positive relationship with employee job satisfaction in selected commercial banks in Kenya; down scoping had a significant positive relationship and business Process reengineering had a significant positive relationship with employee job satisfaction in selected commercial banks in Kenya.
The objective of the research was to establish the Effect of Internal Controls on Financial Performance of Commercial Banks in Kenya. Internal Controls were measured using the five elements of internal control as stipulated by the Committee of Sponsoring organizations of Treadway Commission framework of internal controls while Financial Performance was measured using the historical average of Return on Equity. A descriptive research design was adopted due to its ability to describe the relationship between elements of Internal Controls and Financial Performance. The study used the 43 commercial banks in Kenya. Primary data was collected using a structured questionnaire. Descriptive statistics obtained from data analysis were presented using frequency tables, while inferential data findings were presented using correlation and regression tables. The study findings revealed that the banking sector enjoys a strong financial performance partly because of implementing and maintaining effective internal controls. The existence of effective internal control is attributed to the highly regulated and structured environment in the banking sector. The study recommends banks should effectively implement and maintain internal controls due to the nature of the riskiness of the banking sector and its impact on financial performance.
Most public institutions of higher learning across the world have reported suboptimal financial performance compared to private institutions of higher learning. The poor financial performance can be attributed to financial management practice. The sound financial management practices require the institutions of robust internal control systems. However, there are limited empirical research findings regarding the relationship between the internal control system and financial performance. The specific objectives of the study were: to determine the effect of control activities, risk assessment, control environment, information and communication and monitoring on financial performance of institutions of higher learning in Vihiga County, Kenya. The study was anchored on agency theory, stewardship theory, positive accounting theory and attribution theory. The study used a descriptive research design. The target population of respondents was 140 employees in the four institutions studied whereas the sample size was 96 employees. Primary data was collected from sample population using semi-structured questionnaires. Descriptive and multiple regression analysis were used to analyze data. The study found that the institutions had adequate and effective control activities which included regular internal audit reports, adequate segregation of duties in the finance and accounts departments and physical controls to prevent excess allocated funds. Control activities were found to have a positive significant effect on the financial performance of the institutions under study. The study found that the institutions under study had proper risk assessment tools and risk assessment management system because they carried out continuous financial assessment of their organizations coupled with regular, timely and profound audits. Risk assessment was found to have a positive significant effect on the financial performance of the institutions under study. The study established that the institutions had effective control environment. The number of staff in finance and audit departments was adequate and well trained on accounting and financial management system. Control environment was found to have a positive and significant effect on the financial performance of the institutions under study. The study found that the institutions had effective flow of information and communication channels. In addition, the study found that effective flow of information and communication enhanced financial accountability and financial performance of the institutions. The expenditure of the institutions was properly monitored and audit departments were independent. Financial monitoring was found to have a positive and significant effect on the financial performance of the institutions under study. To the management of the public institutions of higher learning, the study recommends regular and timely financial audit to help them identify any loop holes in their financial systems as well as financial performance.
Before the introduction of micro prudential regulations, some banks experienced delinquency issues that really put to risk customers " funds and raised customer exploitation concerns. With the introduction of bank specific guidelines by the bank regulatory authorities, some banks faced liquidation risks because of adverse effects of stringent micro prudential regulations, thus making micro prudential regulations an intolerable monster in the banking industry. The objective of this study was to establish if there is a relationship between bank specific guidelines and financial performance of Commercial Banks in Kenya. The study adopted a descriptive research design. The population of study was 95 top management employees in the 19 branches of Kenya Commercial Banks in Nairobi County and the period of study was from 2010 to 2017. The study mainly used primary data. A linear regression model of financial performance versus regulations was then applied to examine the effect of banking regulations on financial performance of commercial banks in Kenya. The study findings indicated that there is a positive and significant effect of loan management policies (Beta = 0.478, Sig = 0.000), liquidity management (Beta = 0.243, Sig = 0.000), capital adequacy (Beta = 0.324, Sig = 0.000) and management quality (Beta = 0.461, Sig = 0.008) on financial performance of commercial banks in Kenya. However, asset quality does not have a significant effect on financial performance of commercial banks in Kenya (Beta = 0.101, Sig = 0.362). The study concluded that favorable bank specific regulations can positively improve the performance of commercial banks in Kenya. The study recommends commercial banks to come up with better policies to cope with the central bank of Kenya bank specific regulations in order to improve their performance.
International Journal of Academics & Research, IJARKE Journals
In the recent past the Kenyan banks have experienced a number of corporate failures related to transparency and accountability, their attention was focused on corporate governance matters instead of risk based audit. In 2016, Chase bank, Dubai bank and Imperial bank was positioned under financial management statutory due to suspicions of money laundering and fraud. The purpose of this study was the analysis of risk maturity assessment on audit quality of Tier I commercial banks in Kenya. Specifically to establish the influence of periodic risk audit planning on audit quality; to establish the influence of individual audit assignment on audit quality of tier I commercial banks in Kenya. Descriptive research design was adopted. The study targeted a population of 1597 staffs who constituted respondents from, accounting and finance, internal audit and Risk and compliance department of tier I commercial banks in Kenya. Stratified random sampling was used to select a sample of 104 respondents. Structured questionnaire was used to collect data. Data was analysed by use of inferential and descriptive statistics. Tables was used for data presentation since it is to understand and internalize data and primary data was used. Pilot study was conducted in tier two commercial banks in head office, Nairobi. The internal consistency was tested by use of Cronbach (Alpha – α) model with the alpha coefficient of above 0.7 being considered reliable. Multiple regression analysis was used to determine the strength and direction of the relationship between the independent variables and the dependent variables. These correlations were further subjected to significance test to determine whether the observed correlations were significant. A significance level of 0.05 was therefore set for testing the research hypotheses. The study revealed that Risk Maturity Assessment had the highest coefficient, Beta = 0.261, followed by Periodic risk audit planning with Beta = 0.207 and lastly Individual audit assignment with Beta = 0.174; this indicates that Risk Maturity Assessment makes the strongest unique contribution in explaining the quality of audit in Tier I Commercial Banks in Kenya, Periodic risk audit planning had the second largest unique contribution while Individual audit assignment had the least unique contribution in explaining the variation in the quality of audit in Tier I Commercial Banks in Kenya, Periodic risk audit planning. Among the three predictor variables, Risk Maturity Assessment was found to be the strongest predictor of the quality of audit in Tier I Commercial Banks in Kenya, followed by Periodic risk audit planning risk planning, and lastly Individual audit assignment. The study findings are expected to be of value to the banks stakeholders and form a basis for improving audit quality of banks by enhancing risk based audit. The study concludes that risk based auditing through risk assessment, Periodic risk based planning and individual audit assignment should be enhanced. This would enable the commercial banks to be able to detect risks on time and concentrate on high risk areas leading to increased transparency and accountability, hence enhancing financial performance and audit quality. The study recommends that management in commercial banks in Kenya should adopt effective risk based audit practices such as risk assessment, periodic risk based planning and individual audit assignment to enhance effective and efficient audit reports.The study recommends that the management of commercial banks should consider risk based audit in auditing process and risk management.
The objective of the study was to establish the adequacy of existing cash control system and its effect on the performance of banks in Kenya. The study used descriptive survey as a research design. The target population of this study comprised of 60 respondents drawn from ten commercial banks in Eldoret town, Uasin Gishu County. Data was collected by use of questionnaires and analyzed in excel spreadsheets then presented in tables. The study findings showed that adequacy of exiting internal control system improves performance of the firm. The study recommended that, management of banking sector should involve all the stakeholders that is employees in the organization while carrying out internal control so as to improve its adequacy for the organization and oversee its projected profits. The organization should also benchmark from other successful organization with successful internal control system
Ojo A D U R A G B E M I Sunday
This research examined the effect of internal audit in financial performance of commercial bank, a case study of United Bank for Africa. Specifically, the study detect the level of practice and internal audit function in the commercial banks operating in Nigeria, it identify the level of improvement in the financial performance of commercial banks operating in Nigeria and finally it improve the financial performance of commercial banks operating in Nigeria,. Both primary and secondary sources of data were adhered to on the course of this study and the attitude and responses of those interviewed were noted. The sample size for this study is fifty (50) staff of First Bank Nigeria Plc. Data was obtained through questionnaire and oral interviews. The data that will be collected from various sources, will be analyze using the following statistical measurement are simple percentage and chi-square (X2). The study also reveals that frauds are identified by the internal audit function. Findings show that the standard for audits and audit-related services influence the performance of commercial banks. Finally findings show that there is financial performance of commercial banks operating in Nigeria. It was recommended that the salaries department should keep a history record of engagement, retirement or dismissal, salaries and deduction of each employee.
International Journal of Current Aspects
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Architecture Student Chronicles
Assumptions in a case study
How to conduct a case study.
When students begin studying Architecture at a University, the first thing that they are supposed to become excellent at, is doing a documentation or a case study . It could be a case study of a small village, town, a villa, a bus-stop, or a high-rise commercial or residential building. A case study is an in-depth investigation of a single individual, group, incident, or community. Other ways include experiments, surveys , or analysis of archival information
What is the purpose of conducting a Case Study?
As the term Case Study suggests, it is the study of a particular case that is similar to your topic of design project. Doing a case study will help you understand the various aspects that you have to consider while designing.
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