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Overview

Why are David Moore's statistics books so successful? They have become the books to beat because Moore was the first author to present the teaching of statistics as a useful tool in practice. Unlike traditional statistics books, Moore's texts use real data and walk the student through the process of analyzing that data, as opposed to emphasizing formulas, drill-like exercises, and cookbook mathematics. Thus, for the first time, students learn to think like practicing statisticians and to apply what they learn to their lives.

When Moore and McCabe's Introduction to the Practice of Statistic (IPS) became the #1 book in the market about 5 years ago, statistics instructors realized that a shorter, lower-level, less detailed book based on IPS would also succeed. Hence, David Moore envisioned The Basic Practice of Statistics (BPS)—a text that applies the data analysis approach of IPS but is targeted for a one-term course only. BPS has now become the book to beat, being an ideal match for more schools than any other book in the market.

The second edition of The Basic Practice of Statistics builds on the strengths of the first: a balanced and modern approach to data analysis, data production, and inference; and an emphasis on clear explanations of ideas rather than formal mathematics or reliance on recipes. Moore's use of real world data and examples and his emphasis on statistical thinking show students how statistics can be used as a powerful tool for understanding the world we live in. Designed for students with a limited background in mathematics, The Basic Practice of Statistics 2/e is the ideal way to introduce the core concepts of statistics to the students of today and tomorrow.

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Product Details

  • ISBN-13: 9781429224253
  • Publisher: Freeman, W. H. & Company
  • Publication date: 1/15/2009
  • Edition description: Fifth Edition
  • Edition number: 5
  • Pages: 704
  • Product dimensions: 8.50 (w) x 9.90 (h) x 1.10 (d)

Meet the Author

David S. Moore is Shanti S. Gupta Distinguished Professor of Statistics, Emeritus, at Purdue University and was 1998 president of the American Statistical Association. He received his A.B. from Princeton and his Ph.D. from Cornell, both in mathematics. He has written many research papers in statistical theory and served on the editorial boards of several major journals. Professor Moore is an elected fellow of the American Statistical Association and of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He has served as program director for statistics and probability at the National Science Foundation.  In recent years, Professor Moore has devoted his attention to the teaching of statistics. He was the content developer for the Annenberg/Corporation for Public Broadcasting college-level telecourse Against All Odds: Inside Statistics and for the series of video modules Statistics: Decisions through Data, intended to aid the teaching of statistics in schools. He is the author of influential articles on statistics education and of several leading texts. Professor Moore has served as president of the International Association for Statistical Education and has received the Mathematical Association of America’s national award for distinguished college or university teaching of mathematics.

William I. Notz is Professor of Statistics at the Ohio State University.  He received his B.S. in physics from the Johns Hopkins University and his Ph.D. in mathematics from Cornell University.  His first academic job was as an assistant professor in the Department of Statistics at Purdue University.  While there, he taught the introductory concepts course with Professor Moore and as a result of this experience he developed an interest in statistical education.  Professor Notz is a co-author of EESEE (the Electronic Encyclopedia of Statistical Examples and Exercises) and co-author of Statistics: Concepts and Controversies.

 
Professor Notz’s research interests have focused on experimental design and computer experiments.  He is the author of several research papers and of a book on the design and analysis of computer experiments.  He is an elected fellow of the American Statistical Association.  He has served as the editor of the journal Technometrics and as editor of the Journal of Statistics Education.  He has served as the Director of the Statistical Consulting Service, as acting chair of the Department of Statistics for a year, and as an Associate Dean in the College of Mathematical and Physical Sciences at the Ohio State University.  He is a winner of the Ohio State University’s Alumni Distinguished Teaching Award. 
 

Michael A. Fligner is an Adjunct Professor at the University of California at Santa Cruz and a non-resident Professor Emeritus with the Ohio State University. He received his B.S. in mathematics from the State University of New York at Stony Brook and his Ph.D. from the University of Connecticut. He spent almost 40 years at the Ohio State University where he was Vice Chair of the Department for over 10 years and also served as Director of the Statistical Consulting Service. He has done consulting work with several large corporations in Central Ohio. Professor Fligner's research interests are in Nonparametric Statistical methods and he received the Statistics in Chemistry award from the American Statistical Association for work on detecting biologically active compounds. He is co-author of the book Statistical Methods for Behavioral Ecology and received a Fulbright scholarship under the American Republics Research program to work at the Charles Darwin Research Station in the Galapagos Islands. He has been an Associate Editor of the Journal of Statistical Education. Professor Fligner is currently associated with the Center for Statistical Analysis in the Social Sciences at the University of California at Santa Cruz.

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Table of Contents

Introduction: Statistical Thinking

PART 1. UNDERSTANDING DATA
   1. Examining Distributions

       Introduction
       1.1 Displaying Distributions with Graphs
       1.2 Describing Distributions with Numbers
       1.3 The Normal Distributions
        1.4 Statistics in Summary

    2. Examining Relationships
        Introduction
        2.1 Scatterplots
        2.2 Correlation
        2.3 Least-Square Regression
        2.4 Causations About Correlation and Regression
        2.5 Relations in Categorical Data*
        2.6 Statistics in Summary

    3. Producing Data
        Introduction
        3.1 Designing Samples
        3.2 Designing Experiments
        3.3 Statistics in Summary

PART 2. UNDERSTANDING INFERENCE
    4. Probability and Sampling Distributions

        Introduction
        4.1 Randomness
        4.2 Probability Models
        4.3 Sampling Distributions
        4.4 Control Charts (available on The Basic Practice of Statistics CD-ROM)
        4.5 Statistics in Summary

    5. Probability Theory*
        Introduction
        5.1 General Probability Rules
        5.2 The Binomial Distributions
        5.3 Conditional Probability
        5.4 Statistics in Summary
        5.5 Control Charts (available on the CD-ROM only)

    6. Introduction to Inference
        Introduction
        6.1 Estimating with Confidence
        6.2 Tests of Significance
        6.3 Using Significance Tests
        6.4 Error Probabilities and Power*
        6.5 Statistics in Summary

    7. Inference for Distributions
        Introduction
        7.1 Inference for the Mean of a Population
        7.2 Comparing Two Means
        7.3 Inference for Population Spread
        7.4 Statistics in Summary

    8. Inference for Proportions
        Introduction
        8.1 Inference for a Population Proportion
        8.2 Comparing Two Proportions
        8.3 Statistics in Summary

PART 3. TOPICS IN INFERENCE
    9. Inference for Two-Way Tables

        Introduction
        Statistics in Summary

    10. One-Way Analysis of Variance: Comparing Several Means
        Introduction
        Statistics in Summary

    11. Inference for Regression
        Introduction
        Statistics in Summary

    12. Nonparametric Tests (available on the CD-ROM only)

Notes and Data Sources
Tables
A Standard normal probabilities
B Random digits
C t distribution critical values
D F distribution critical values
E Chi-square distribution critical values

(Optional material in Chapters 1 to 8 is marked with an asterisk (*). Note that Chapter 5 is entirely optional.)
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