problems and solutions in mathematical statistics pdf

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• Dr. Jeremy Orloff
• Jonathan Bloom

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• Mathematics

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• Mathematics Discrete Mathematics Probability and Statistics

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Introduction to probability and statistics.

Listed in the following table are practice exam questions and solutions, and the exam questions and solutions. Additional materials for exam preparation can be found under the class sessions dedicated to exam review. Students were encouraged to prepare a 4x6 inch notecard to use for reference during each exam.

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Problems In Probability Theory, Mathematical Statistics And Theory Of Random Functions

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Examples and Problems in Mathematical Statistics by Shelemyahu Zacks

2014, International Statistical Review

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• © 1973

Statistics: Problems and Solutions

• J. Murdoch 0 ,
• J. A. Barnes 1

Cranfield Institute of Technology, UK

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8 Citations

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• Table of contents

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Table of contents (9 chapters)

Front matter, probability theory.

J. Murdoch, J. A. Barnes

Theory of distributions

Hypergeometric, binomial and poisson distributions, normal distribution, relationship between the basic distributions, distribution of linear functions of variables, estimation and significance testing (i)—‘large sample’ methods, sampling theory and significance testing (ii)—‘t’, ‘f’ and x2 tests, linear regression theory.

• conditional probability
• normal distribution
• Poisson distribution
• probability
• probability distribution
• probability theory
• standard deviation

Book Title : Statistics: Problems and Solutions

Authors : J. Murdoch, J. A. Barnes

DOI : https://doi.org/10.1007/978-1-349-01063-9

Publisher : Palgrave Macmillan London

eBook Packages : Mathematics and Statistics , Mathematics and Statistics (R0)

Copyright Information : J. Murdoch and J. A. Barnes 1973

Softcover ISBN : 978-0-333-12017-0 Published: 18 June 1973

eBook ISBN : 978-1-349-01063-9 Published: 18 June 1973

Edition Number : 1

Number of Pages : XII, 225

Topics : Probability Theory and Stochastic Processes

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Sultan Chand & Sons

Publishers of Standard Educational Textbooks

Problems & Solutions in Mathematical Statistics

Quick Overview

Authored By

Gupta SC , Gupta Vikas , Gupta Sanjeev Kumar

Publisher: Sultan Chand & Sons

Publishing Year: 2016

Size (mm): 24.00 x 18.00

ISBN: 93-5161-086-1

Page nos.: viii + 640

MRP: 495.00

Subject: Mathematical Sciences

• Book Summary
• Book Content
• Additional Information

This book is modest though determined bid to serve as a self – study for Undergraduate and Post – Graduate Courses in Statistics /Mathematics/ Economics/ Operations Research /MCA of Indian Universities and also for those preparing for competitive examinations like Indian Civil Services, Indian Statistical Service and other examinations conducted by Indian Statistical Institute, RBI, Institute of Actuaries, CSIR, etc.

• Descriptive Measures [Measures of Central Tendency‚ Dispersion‚ Skewness and Kurtosis ]
• Probability
• Random Variables and Distribution Functions
• Mathematical Expectation
• Generating Functions and Law of Large Numbers
• Discrete Probability Distributions
• Continuous Probability Distributions
• Correlation
• Bivariate Normal Distribution
• Exact Sampling Distributions-(I) (Chi-Square Distribution)
• Exact Sampling Distributions- (II) (T and F Distributions)

ISBN13: 978-93-5161-086-1

Weight: 890.00

Edition: 1st Edition

Language: English

Title Code: 1232

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Sir I have gone through some chapters of the book. The book definitely covers a large area of Statistics, which is not very common in other such books. It is an excellent mixture of both theories and solved problems. Most chapter has some unsolved problems for advanced learners. Some hints in some of the unsolved problems should have been better. The extent of typographical error in the book is minimum and this a clear indication that the proofreading has been excellent. Another unique feature of the book is the NET solved problems. This shall be of real use to the students and teachers. i just wish is the number of such problems would be more in number and if it would be there in all the chapters. Sir these days as you know student do not read much so some more elaboration why some statistical procedures are required or why they arise might further enrich the already enriched text. Overall the book has sufficient material to be a text book for honours standard. The book also covers some part of master degree- making it well suitable for a reference book for m sc program of any Indian university.

good for practicing new problems in mathematics and statistics

One of the best books.

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• Introduction
• 1.1 Definitions of Statistics, Probability, and Key Terms
• 1.2 Data, Sampling, and Variation in Data and Sampling
• 1.3 Frequency, Frequency Tables, and Levels of Measurement
• 1.4 Experimental Design and Ethics
• 1.5 Data Collection Experiment
• 1.6 Sampling Experiment
• Chapter Review
• Bringing It Together: Homework
• 2.1 Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs
• 2.2 Histograms, Frequency Polygons, and Time Series Graphs
• 2.3 Measures of the Location of the Data
• 2.4 Box Plots
• 2.5 Measures of the Center of the Data
• 2.6 Skewness and the Mean, Median, and Mode
• 2.7 Measures of the Spread of the Data
• 2.8 Descriptive Statistics
• Formula Review
• 3.1 Terminology
• 3.2 Independent and Mutually Exclusive Events
• 3.3 Two Basic Rules of Probability
• 3.4 Contingency Tables
• 3.5 Tree and Venn Diagrams
• 3.6 Probability Topics
• Bringing It Together: Practice
• 4.1 Probability Distribution Function (PDF) for a Discrete Random Variable
• 4.2 Mean or Expected Value and Standard Deviation
• 4.3 Binomial Distribution
• 4.4 Geometric Distribution
• 4.5 Hypergeometric Distribution
• 4.6 Poisson Distribution
• 4.7 Discrete Distribution (Playing Card Experiment)
• 4.8 Discrete Distribution (Lucky Dice Experiment)
• 5.1 Continuous Probability Functions
• 5.2 The Uniform Distribution
• 5.3 The Exponential Distribution
• 5.4 Continuous Distribution
• 6.1 The Standard Normal Distribution
• 6.2 Using the Normal Distribution
• 6.3 Normal Distribution (Lap Times)
• 6.4 Normal Distribution (Pinkie Length)
• 7.1 The Central Limit Theorem for Sample Means (Averages)
• 7.2 The Central Limit Theorem for Sums
• 7.3 Using the Central Limit Theorem
• 7.4 Central Limit Theorem (Pocket Change)
• 7.5 Central Limit Theorem (Cookie Recipes)
• 8.1 A Single Population Mean using the Normal Distribution
• 8.2 A Single Population Mean using the Student t Distribution
• 8.3 A Population Proportion
• 8.4 Confidence Interval (Home Costs)
• 8.5 Confidence Interval (Place of Birth)
• 8.6 Confidence Interval (Women's Heights)
• 9.1 Null and Alternative Hypotheses
• 9.2 Outcomes and the Type I and Type II Errors
• 9.3 Distribution Needed for Hypothesis Testing
• 9.4 Rare Events, the Sample, Decision and Conclusion
• 9.5 Additional Information and Full Hypothesis Test Examples
• 9.6 Hypothesis Testing of a Single Mean and Single Proportion
• 10.1 Two Population Means with Unknown Standard Deviations
• 10.2 Two Population Means with Known Standard Deviations
• 10.3 Comparing Two Independent Population Proportions
• 10.4 Matched or Paired Samples
• 10.5 Hypothesis Testing for Two Means and Two Proportions
• 11.1 Facts About the Chi-Square Distribution
• 11.2 Goodness-of-Fit Test
• 11.3 Test of Independence
• 11.4 Test for Homogeneity
• 11.5 Comparison of the Chi-Square Tests
• 11.6 Test of a Single Variance
• 11.7 Lab 1: Chi-Square Goodness-of-Fit
• 11.8 Lab 2: Chi-Square Test of Independence
• 12.1 Linear Equations
• 12.2 Scatter Plots
• 12.3 The Regression Equation
• 12.4 Testing the Significance of the Correlation Coefficient
• 12.5 Prediction
• 12.6 Outliers
• 12.7 Regression (Distance from School)
• 12.8 Regression (Textbook Cost)
• 12.9 Regression (Fuel Efficiency)
• 13.1 One-Way ANOVA
• 13.2 The F Distribution and the F-Ratio
• 13.3 Facts About the F Distribution
• 13.4 Test of Two Variances
• 13.5 Lab: One-Way ANOVA
• A | Review Exercises (Ch 3-13)
• B | Practice Tests (1-4) and Final Exams
• C | Data Sets
• D | Group and Partner Projects
• E | Solution Sheets
• F | Mathematical Phrases, Symbols, and Formulas
• G | Notes for the TI-83, 83+, 84, 84+ Calculators

AIDS patients.

The average length of time (in months) AIDS patients live after treatment.

X = the length of time (in months) AIDS patients live after treatment

• 823,088 823,856 823,088 823,856
• quantitative discrete
• quantitative continuous
• In both years, underwater earthquakes produced massive tsunamis.

simple random

values for X , such as 3, 4, 11, and so on

No, we do not have enough information to make such a claim.

Take a simple random sample from each group. One way is by assigning a number to each patient and using a random number generator to randomly select patients.

This would be convenience sampling and is not random.

Yes, the sample size of 150 would be large enough to reflect a population of one school.

Even though the specific data support each researcher’s conclusions, the different results suggest that more data need to be collected before the researchers can reach a conclusion.

There is not enough information given to judge if either one is correct or incorrect.

The software program seems to work because the second study shows that more patients improve while using the software than not. Even though the difference is not as large as that in the first study, the results from the second study are likely more reliable and still show improvement.

Yes, because we cannot tell if the improvement was due to the software or the exercise; the data is confounded, and a reliable conclusion cannot be drawn. New studies should be performed.

No, even though the sample is large enough, the fact that the sample consists of volunteers makes it a self-selected sample, which is not reliable.

No, even though the sample is a large portion of the population, two responses are not enough to justify any conclusions. Because the population is so small, it would be better to include everyone in the population to get the most accurate data.

• Inmates may not feel comfortable refusing participation, or may feel obligated to take advantage of the promised benefits. They may not feel truly free to refuse participation.
• Parents can provide consent on behalf of their children, but children are not competent to provide consent for themselves.
• All risks and benefits must be clearly outlined. Study participants must be informed of relevant aspects of the study in order to give appropriate consent.
• all children who take ski or snowboard lessons
• a group of these children
• the population mean age of children who take their first snowboard lesson
• the sample mean age of children who take their first snowboard lesson
• X = the age of one child who takes his or her first ski or snowboard lesson
• values for X , such as 3, 7, and so on
• the clients of the insurance companies
• a group of the clients
• the mean health costs of the clients
• the mean health costs of the sample
• X = the health costs of one client
• values for X , such as 34, 9, 82, and so on
• all the clients of this counselor
• a group of clients of this marriage counselor
• the proportion of all her clients who stay married
• the proportion of the sample of the counselor’s clients who stay married
• X = the number of couples who stay married
• all people (maybe in a certain geographic area, such as the United States)
• a group of the people
• the proportion of all people who will buy the product
• the proportion of the sample who will buy the product
• X = the number of people who will buy it
• buy, not buy

quantitative discrete, 150

qualitative, Oakland A’s

quantitative discrete, 11,234 students

qualitative, Crest

quantitative continuous, 47.3 years

• The survey was conducted using six similar flights. The survey would not be a true representation of the entire population of air travelers. Conducting the survey on a holiday weekend will not produce representative results.
• Conduct the survey during different times of the year. Conduct the survey using flights to and from various locations. Conduct the survey on different days of the week.

Answers will vary. Sample Answer: You could use a systematic sampling method. Stop the tenth person as they leave one of the buildings on campus at 9:50 in the morning. Then stop the tenth person as they leave a different building on campus at 1:50 in the afternoon.

Answers will vary. Sample Answer: Many people will not respond to mail surveys. If they do respond to the surveys, you can’t be sure who is responding. In addition, mailing lists can be incomplete.

convenience cluster stratified systematic simple random

• qualitative

Causality: The fact that two variables are related does not guarantee that one variable is influencing the other. We cannot assume that crime rate impacts education level or that education level impacts crime rate.

Confounding: There are many factors that define a community other than education level and crime rate. Communities with high crime rates and high education levels may have other lurking variables that distinguish them from communities with lower crime rates and lower education levels. Because we cannot isolate these variables of interest, we cannot draw valid conclusions about the connection between education and crime. Possible lurking variables include police expenditures, unemployment levels, region, average age, and size.

• Possible reasons: increased use of caller id, decreased use of landlines, increased use of private numbers, voice mail, privacy managers, hectic nature of personal schedules, decreased willingness to be interviewed
• When a large number of people refuse to participate, then the sample may not have the same characteristics of the population. Perhaps the majority of people willing to participate are doing so because they feel strongly about the subject of the survey.

The sum of the travel times is 1,173.1. Divide the sum by 50 to calculate the mean value: 23.462. Because each state’s travel time was measured to the nearest tenth, round this calculation to the nearest hundredth: 23.46.

Explanatory variable: amount of sleep Response variable: performance measured in assigned tasks Treatments: normal sleep and 27 hours of total sleep deprivation Experimental Units: 19 professional drivers Lurking variables: none – all drivers participated in both treatments Random assignment: treatments were assigned in random order; this eliminated the effect of any “learning” that may take place during the first experimental session Control/Placebo: completing the experimental session under normal sleep conditions Blinding: researchers evaluating subjects’ performance must not know which treatment is being applied at the time

You cannot assume that the numbers of complaints reflect the quality of the airlines. The airlines shown with the greatest number of complaints are the ones with the most passengers. You must consider the appropriateness of methods for presenting data; in this case displaying totals is misleading.

Answers will vary. Sample answer: The sample is not representative of the population of all college textbooks. Two reasons why it is not representative are that he only sampled seven subjects and he only investigated one textbook in each subject. There are several possible sources of bias in the study. The seven subjects that he investigated are all in mathematics and the sciences; there are many subjects in the humanities, social sciences, and other subject areas, (for example: literature, art, history, psychology, sociology, business) that he did not investigate at all. It may be that different subject areas exhibit different patterns of textbook availability, but his sample would not detect such results.

He also looked only at the most popular textbook in each of the subjects he investigated. The availability of the most popular textbooks may differ from the availability of other textbooks in one of two ways:

• the most popular textbooks may be more readily available online, because more new copies are printed, and more students nationwide are selling back their used copies OR
• the most popular textbooks may be harder to find available online, because more student demand exhausts the supply more quickly.

In reality, many college students do not use the most popular textbook in their subject, and this study gives no useful information about the situation for those less popular textbooks.

He could improve this study by:

• expanding the selection of subjects he investigates so that it is more representative of all subjects studied by college students, and
• expanding the selection of textbooks he investigates within each subject to include a mixed representation of both the most popular and less popular textbooks.

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Access for free at https://openstax.org/books/introductory-statistics/pages/1-introduction

• Authors: Barbara Illowsky, Susan Dean
• Publisher/website: OpenStax
• Book title: Introductory Statistics
• Publication date: Sep 19, 2013
• Location: Houston, Texas
• Book URL: https://openstax.org/books/introductory-statistics/pages/1-introduction
• Section URL: https://openstax.org/books/introductory-statistics/pages/1-solutions

© Jun 23, 2022 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.