Probability and Statistical Inference (8th Edition) [Hardcover]

Robert V. Hogg (Author), Elliot Tanis (Author)

Book Description

Publication Date: January 7, 2009 | ISBN-10: 0321584759 | ISBN-13: 978-0321584755 | Edition: 8

BOOK DESCRIPTION:

Written by two leading statisticians, this applied introduction to the mathematics of probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.

 

NEW TO THIS EDITION:

• The included CD-ROM contains all of the data sets in a variety of formats for use with most statistical software packages. This disc also includes several applications of Minitab^® and Maple^™.
• Historical vignettes at the end of each chapter outline the origin of the greatest accomplishments in the field of statistics, adding enrichment to the course.

 Content updates

• The first five chapters have been reorganized to cover a standard probability course with more real examples and exercises. These chapters are important for students wishing to pass the first actuarial exam, and cover the necessary material needed for students taking this course at the junior level.
• Chapters 6 and 7 on estimation and tests of statistical hypotheses tie together confidence intervals and tests, including one-sided ones. There are separate chapters on nonparametric methods, Bayesian methods, and Quality Improvement.
• Chapters 4 and 5 include a strong discussion on conditional distributions and functions of random variables, including Jacobians of transformations and the moment-generating technique. Approximations of distributions like the binomial and the Poisson with the normal can be found using the central limit theorem.
• Chapter 8 (Nonparametric Methods) includes most of the standards tests such as those by Wilcoxon and also the use of order statistics in some distribution-free inferences.
• Chapter 9 (Bayesian Methods) explains the use of the "Dutch book" to prove certain probability theorems.
• Chapter 11 (Quality Improvement) stresses how important W. Edwards Deming's ideas are in understanding variation and how they apply to everyday life.

TABLE OF CONTENTS: 

Preface

Prologue

 

1. Probability

1.1 Basic Concepts

1.2 Properties of Probability

1.3 Methods of Enumeration

1.4 Conditional Probability

1.5 Independent Events

1.6 Bayes's Theorem

 

2. Discrete Distributions

2.1 Random Variables of the Discrete Type

2.2 Mathematical Expectation

2.3 The Mean, Variance, and Standard Deviation

2.4 Bernoulli Trials and the Binomial Distribution

2.5 The Moment-Generating Function

2.6 The Poisson Distribution

 

3. Continuous Distributions

3.1 Continuous-Type Data

3.2 Exploratory Data Analysis

3.3 Random Variables of the Continuous Type

3.4 The Uniform and Exponential Distributions

3.5 The Gamma and Chi-Square Distributions

3.6 The Normal Distribution

3.7 Additional Models

 

4. Bivariate Distributions

4.1 Distributions of Two Random Variables

4.2 The Correlation Coefficient

4.3 Conditional Distributions

4.4 The Bivariate Normal Distribution

 

5. Distributions of Functions of Random Variables

5.1 Functions of One Random Variable

5.2 Transformations of Two Random Variables

5.3 Several Independent Random Variables

5.4 The Moment-Generating Function Technique

5.5 Random Functions Associated with Normal Distributions

5.6 The Central Limit Theorem

5.7 Approximations for Discrete Distributions

 

6. Estimation

6.1 Point Estimation

6.2 Confidence Intervals for Means

6.3 Confidence Intervals for Difference of Two Means

6.4 Confidence Intervals for Variances

6.5 Confidence Intervals for Proportions

6.6 Sample Size.

6.7 A Simple Regression Problem

6.8 More Regression

 

7. Tests of Statistical Hypotheses

7.1 Tests about Proportions

7.2 Tests about One Mean

7.3 Tests of the Equality of Two Means

7.4 Tests for Variances

7.5 One-Factor Analysis of Variance

7.6 Two-Factor Analysis of Variance

7.7 Tests Concerning Regression and Correlation

 

8. Nonparametric Methods

8.1 Chi-Square Goodness of Fit Tests

8.2 Contingency Tables

8.3 Order Statistics

8.4 Distribution-Free Confidence Intervals for Percentiles

8.5 The Wilcoxon Tests

8.6 Run Test and Test for Randomness

8.7 Kolmogorov-Smirnov Goodness of Fit Test

8.8 Resampling Methods

 

9. Bayesian Methods

9.1 Subjective Probability

9.2 Bayesian Estimation

9.3 More Bayesian Concepts

 

10. Some Theory

10.1 Sufficient Statistics

10.2 Power of a Statistical Test

10.3 Best Critical Regions

10.4 Likelihood Ratio Tests

10.5 Chebyshev's Inequality and Convergence in Probability

10.6 Limiting Moment-Generating Functions

10.7 Asymptotic Distributions of Maximum Likelihood Estimators

 

11. Quality Improvement Through Statistical Methods

11.1 Time Sequences

11.2 Statistical Quality Control

11.3 General Factorial and 2^k Factorial Designs

11.4 Understanding Variation

 

A. Review of Selected Mathematical Techniques

      A.1 Algebra of Sets

      A.2 Mathematical Tools for the Hypergeometric Distribution

      A.3 Limits

      A.4 Infinite Series

      A.5 Integration

      A.6 Multivariate Calculus

B. References

C. Tables

D. Answers to Odd-Numbered Exercises

Editorial Reviews

Review

"Generally, I think the pedagogy is excellent, providing an almost holistic introduction to statistics, both its mathematical and applications sides. Elements of the subject are introduced in increasing layers of complexity, at a rate that is challenging yet measured. Masterfully done. My overall impression of the book is quite favorable and actually I am considering this text for my next cycle of classes. Strengths: excellent use of examples to illustrate concepts; strong exercise selections; the discussions are generally clear, animated, and focused with the main drive of the text in mind. All the necessary topics central to modern statistics are introduced. The level of the text is quite good for an undergraduate introductory course. Many rather difficult ideas are presented simply, but effectively enough to prepare students for later topics and courses. And the text really bares the soul of statistics. The text motivates the theory by keeping it connected to real-world applications." — David F. Snyder, Texas State University

"Probability and Statistical Inference is a great text to use for a one-year course, where the students are just becoming mathematically prepared. The authors write with great care and clearly develop and motivate the subject. This edition also contains a chapter on Bayesian methods. Chapter 7 is an interesting and modern treatment of the subject—a subject that has included some controversy. Although I am a probabilist, I am certainly pleased to see this treatment in an undergraduate text. Bayesian methods have long needed suitable treatment at the undergraduate level. It provides an up-to-date and complete treatment of mathematics of probability and statistics. This edition also includes many new examples, applications, and exercises. Each of these has improved in an already outstanding text." — Randall Swift, California State Polytechnic University, Pomona

"This latest version of Hogg and Tanis contains many more realistic data scenarios that rely much less on coin tossing and dice and card examples. Students will likely better understand the material if they can relate to the examples. The authors strike a good balance between readability and rigor. The material is accurately presented and theorems are accurate. I am glad to see section 6.13 'Resampling Methods' induded. The 'bootstrap' has been around now for 20 years but many mathematical statistics books still neglect it or relegate it to the exercises. This is a good indication that the text is up-to-date." — Paul Joyce, University of Idaho

"This is a good, solid, calculus-based introduction to probability and statistics at the sophomore-junior level. I have used this textbook twice for such a course, and would like to use it again in the future." — Ching-Yuan Chiang, James Madison University

"The examples in the book are very clear and easy to follow. My students would benefit from this book more than our current textbook." — Mark Ghamsary, Loma Linda University

--This text refers to an out of print or unavailable edition of this title.

From the Publisher

An accessible introduction to the mathematics of probability and statistics for students with a background in calculus. Numerous applications help explain and motivate the concepts. --This text refers to an out of print or unavailable edition of this title.

See all Editorial Reviews

Product Details

• Hardcover: 648 pages
• Publisher: Prentice Hall; 8 edition (January 7, 2009)
• Language: English
• ISBN-10: 0321584759
• ISBN-13: 978-0321584755
• Product Dimensions: 10 x 8 x 1.2 inches
• Shipping Weight: 3 pounds (View shipping rates and policies)
• Average Customer Review: 2.2 out of 5 stars  See all reviews (45 customer reviews)
• Amazon Best Sellers Rank: #160,370 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

47 of 50 people found the following review helpful:

2.0 out of 5 stars Not as Good as the 6th Edition!, November 20, 2005

By 

Patrick Goetz "cultural omnivore" (Austin, TX USA) - See all my reviews
(VINE VOICE)    (REAL NAME)   

Amazon Verified Purchase

This review is from: Probability and Statistical Inference (7th Edition) (Hardcover)

I am currently teaching statistics (using a different textbook) and have been using the 6th edition of Hogg/Tanis as a reference. In my opinion, this is a pretty good text for someone who A) already has some idea of what statistics is all about and B) has a thorough understanding of calculus, which Hogg/Tanis make liberal use of. For someone who likes and understands calculus,
this is a much better introductory text than those that studiously avoid any mention of higher level mathematics. I give the 6th edition a 5-star rating based on the sections I've looked at so far.

With that said, I'm sorry to report that the 7th edition is not as good as the 6th. The authors have re-organized the material "for better logical organization", but in the process have lost some pedagogical clarity. For example, the relatively important student's t distribution has been relegated to an obscure example buried in a new chapter on the normal distribution, and the formerly excellent explanation of how this is derived is gone.

And speaking of "The Normal Distribution" chapter, do I really want all things normal relegated to a separate chapter? The pervasive use and importance of this distribution in statistics makes me think that it might be better to let the normal distribution pop up whenever it needs to be invoked, as was the case in the 6th edition. Including a "Sampling Distribution Theory" chapter (as was done in the 6th edition) makes a lot more sense than what they've done now. The new chapter on Bayesian Methods is short, and not terribly useful. Relegating this material to section 9.5 in a chapter on "Theory of Statistical Inference", as was done in the 6th edition was a much better decision.

The section on "Exploratory Data Analysis" (histograms and stemplots) has been moved from an introductory chapter (which no longer exists) to the chapter on "Continuous-Type Data". How does this make any sense? And yes, it is most definately a good idea to have an introductory chapter which talks about basic concepts and data visualizations. In the 7th edition, the mean, median, and standard deviation are first mentioned in chapter 2.

Finally, why on earth do authors think that randomly adding color to a textbook and widening the pages to allow for giant margins on every page makes a text more readable/useful when in fact just the opposite is the case? The wide margins add nothing and make the book both heavier and more unwieldy, and the blue section headings and graphs give it the feel of a junior high school algebra text. The compact elegance of the 6th edition stands in stark contrast to the large and comparatively garish 7th edition.

This revision has all the feel of something that was driven strictly by textbook marketing concerns and has nothing to do with either pedagogy or an interest in producing a excellent statistics book.

My advice? If you're looking for something for self-study or reference, get the 6th edition instead. It's better, and you can get a used copy on Amazon for next to nothing, since the lemmings have all switched to using the 7th edition and there are a lot of unwanted copies of the 6th floating around.

The nonsense of constantly producing new (and often inferior) editions of textbooks just so that publishers can make more money needs to be nipped in the bud.

14 of 15 people found the following review helpful:

1.0 out of 5 stars Don't buy this book!, December 12, 2000

By 

Robert L. Hill (Milwaukee, WI United States) - See all my reviews

This review is from: Probability and Statistical Inference (6th Edition) (Hardcover)

There are good books on probability and statistical inference. This isn't one of them! If you are hunting for something - look for authors like James T. McClave or P. George Benson. James McClave has written some good books in this area.

Examples are HARD TO FOLLOW. There is no development of concepts. The writer doesn't seem to have any idea how to explain or how to provide examples. THIS IS NOT A BOOK THAT NORMAL PEOPLE CAN UNDERSTAND! IF YOU LIKE MATH OR WOULD LIKE TO UNDERSTAND MATH - DON'T BUY THIS BOOK! It does provide an example of what a book shouldn't look like!

13 of 14 people found the following review helpful:

2.0 out of 5 stars thorough but very confusing and badly written, July 17, 2003

By A Customer

This review is from: Probability and Statistical Inference (6th Edition) (Hardcover)

I taught prob/stat from 99-02. The first year we used Tanis and Hogg 5th, the second 6th Edition, and the last two semesters were the current Larsen and Marx (much nicer IMO, at least on the readability and organization factor). I felt the 6th was a step backwards from the 5th in terms of organization and the 5th wasn't great for that. In fact, the 6th felt a lot more like the old 3rd edition I had when I was taking prob/stat for the very first time. In my experience, many of the flaws that other reviewers have noted are present in this book:

-Confusing transitions between theorems and examples in the main text, with theorems and examples not clearly delineated from surrounding text (particularly where they end), making it hard to use the book for reference as you work problems;
-Examples that have too many steps skipped;
-Problems which are often much more difficult than the examples in the text (that said, many of the problems in T&H are quite good, which I suspect explains the longevity of it as a text, well that, simple inertia among profs who have their lectures already written, and the publisher's sales staff :).

*I* could use it as a reference as it does cover a lot of topics pretty well. So what. If I'm teaching the material I *better* have a mastery over the material in the book! Student have got to be able to use it and they don't have that mastery. Bad organization simply obscures the material which, while not difficult from a straight mathematical standpoint, IS pretty difficulty conceptually IME.