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Elementary Statistics

Elementary Statistics

International Edition
8th Edition

Neil Weiss

Feb 2011, Paperback, 704 pages
ISBN13: 9780321709981
ISBN10: 0321709985
For orders to USA, Canada, Australia, New Zealand or Japan visit your local Pearson website
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Weiss’s Elementary Statistics, Eighth Edition is the ideal textbook for introductory statistics classes that emphasize statistical reasoning and critical thinking. Comprehensive in its coverage, Weiss’s meticulous style offers careful, detailed explanations to ease the learning process. With more than 2,000 exercises, most using real data, there is a wealth of opportunity for students to apply their knowledge and develop statistical literacy. The text is suitable for a one-semester course.

Elementary Statistics, Eighth Edition, contains parallel presentation of critical-value and p-value approaches to hypothesis testing. This unique design allows both the flexibility to concentrate on one approach or the opportunity for greater depth in comparing the two.

This edition of Elementary Statistics continues the book's tradition of being on the cutting edge of statistical pedagogy, technology, and data analysis. It includes hundreds of new and updated exercises with real data from journals, magazines, newspapers, and Web sites.

Elementary Statistics, Eighth Edition, takes a data-driven approach with more than 700 data sets documented by several hundred data sources.

Datasets and other resources (where applicable) for this book are available here.

Preface

Course Management Notes (Instructor’s Edition only)

Supplements

Technology Resources

Data Sources

Part I: Introduction

1. The Nature of Statistics

1.1 Statistics Basics

1.2 Simple Random Sampling

1.3 Other Sampling Designs*

1.4 Experimental Designs*

Part II: Descriptive Statistics

2. Organizing Data

2.1 Variables and Data

2.2 Organizing Qualitative Data

2.3 Organizing Quantitative Data

2.4 Distribution Shapes

2.5 Misleading Graphs*

3. Descriptive Measures

3.1 Measures of Center

3.2 Measures of Variation

3.3 The Five-Number Summary; Boxplots

3.4 Descriptive Measures for Populations; Use of Samples

4. Descriptive Methods in Regression and Correlation

4.1 Linear Equations with One Independent Variable

4.2 The Regression Equation

4.3 The Coefficient of Determination

4.4 Linear Correlation

Part III: Probability, Random Variables, and Sampling Distributions

5. Probability and Random Variables

5.1 Probability Basics

5.2 Events

5.3 Some Rules of Probability

5.4 Discrete Random Variables and Probability Distributions*

5.5 The Mean and Standard Deviation of a Discrete Random Variable*

5.6 The Binomial Distribution*

6. The Normal Distribution

6.1 Introducing Normally Distributed Variables

6.2 Areas Under the Standard Normal Curve

6.3 Working with Normally Distributed Variables

6.4 Assessing Normality; Normal Probability Plots

7. The Sampling Distribution of the Sample Mean

7.1 Sampling Error; the Need for Sampling Distributions

7.2 The Mean and Standard Deviation of the Sample Mean

7.3 The Sampling Distribution of the Sample Mean

Part IV: Inferential Statistics

8. Confidence Intervals for One Population Mean

8.1 Estimating a Population Mean

8.2 Confidence Intervals for One Population Mean When σ Is Known

8.3 Margin of Error

8.4 Confidence Intervals for One Population Mean When σ Is Unknown

9. Hypothesis Tests for One Population Mean

9.1 The Nature of Hypothesis Testing

9.2 Critical-Value Approach to Hypothesis Testing

9.3 P-Value Approach to Hypothesis Testing

9.4 Hypothesis Tests for One Population Mean When σ Is Known

9.5 Hypothesis Tests for One Population Mean When σ Is Unknown

10. Inferences for Two Population Means

10.1 The Sampling Distribution of the Difference between Two Sample Means for Independent Samples

10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal

10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal

10.4 Inferences for Two Population Means, Using Paired Samples

11. Inferences for Population Proportions

11.1 Confidence Intervals for One Population Proportion

11.2 Hypothesis Tests for One Population Proportion

11.3 Inferences for Two Population Proportions

12. Chi-Square Procedures

12.1 The Chi-Square Distribution

12.2 Chi-Square Goodness-of-Fit Test

12.3 Contingency Tables; Association

12.4 Chi-Square Independence Test

12.5 Chi-Square Homogeneity Test

13. Analysis of Variance (ANOVA)

13.1 The F-Distribution

13.2 One-Way ANOVA: The Logic

13.3 One-Way ANOVA: The Procedure

14. Inferential Methods in Regression and Correlation

14.1 The Regression Model; Analysis of Residuals

14.2 Inferences for the Slope of the Population Regression Line

14.3 Estimation and Prediction

14.4 Inferences in Correlation

APPENDICES

Appendix A: Statistical Tables

I. Random numbers

II. Areas under the standard normal curve

III. Normal scores

IV. Values of

V. Values of χα2

VI. Values of

VII. Binomial probabilities

Appendix B Answers to Selected Exercises

Index

Photo Credits

Indexes for Biographical Sketches & Case Studies

WeissStats CD-ROM (included with every new textbook)

Brief Contents

Note: See the WeissStats CD-ROM ReadMe file for detailed contents.

Applets

Data Sets

DDXL (Excel Add-In)

Detailed t and Chi-square Tables

Focus Database

Formulas and Appendix A Tables

Further Topics in Probability

JMP Concept Discovery Modules

Minitab Macros

Technology Basics

TI Programs

*indicates an optional section

  • Real-World Examples illustrate every concept discussed in the text with detailed, compelling examples from real life.
    • You Try It! follows many worked examples, allowing students to immediately check their understanding by directing them to a similar exercise to solve on their own.
  • Real Data Sources help students see the integration of statistics in everyday life. Neil Weiss has included carefully cited data from reputable journals, newspapers, magazines and Web sites.
  • Helpful text features help readers make sense of the material and provide easy reference for study and review.
    • Interpretation Boxes explain the meaning and significance of statistical results in everyday life and highlight the importance of interpreting answers and results.
    • What Does It Mean? boxes explain the meaning of definitions, formulas, and key facts. This feature also summarizes relevant discussions.
    • Procedure Boxes have been enhanced to include the “why, when, and how” of the methods. Each procedure box has a brief identifying title followed by a statement of its purpose (why it’s used), the assumptions for its use (when it’s used), and the steps for applying the procedure (how it’s used).
    • Technology Appendices help students use SPSS, Minitab®, Excel®, and the TI 83/84 Plus graphing calculators. These appendixes, located on the CD-ROM packaged with new copies of the book, introduce the technology and methods for using it to work with data.
  • Parallel Critical-Value/p-Value Approaches offers complete flexibility in the coverage of critical-value and p-value approaches to hypothesis testing. Instructors can focus on one approach or they can compare both approaches.
  • Parallel Presentations of Technology: The Weiss approach offers complete flexibility in the coverage of technology which includes options for the use of Minitab, Excel, and the TI-83 and TI-84 Plus graphing calculators. One or more technologies can be explored and compared. Instructions and output for each package are included in Technology Centers throughout the book.
  • The WeissStats CD-ROM bound inside every new copy of the textbook includes applets, an optional text chapter that presents additional probability and random-variable topics, an introduction to statistical technologies, and DDXL™, an Excel add in. Data sets are provided as text, Minitab, Excel, JMP®, and SPSS® files, as well as in the TI-83/84 Plus graphing calculator list files.
  • Focusing on Data Analysis sections at the end of each chapter examine the Focus Database, a database of 13 variables for the undergraduate students at the University of Wisconsin—Eau Claire. This feature lets students work with large data sets, practice using technology, and discover the many methods of exploring and analyzing data–both descriptively and inferentially.

Neil A. Weiss received his Ph.D. from UCLA and subsequently accepted an assistant-professor position at Arizona State University (ASU), where he was ultimately promoted to the rank of full professor. Dr. Weiss has taught statistics, probability, and mathematics—from the freshman level to the advanced graduate level—for more than 30 years. In recognition of his excellence in teaching, he received the Dean’s Quality Teaching Award from the ASU College of Liberal Arts and Sciences. Dr. Weiss’ comprehensive knowledge and experience ensures that his texts are mathematically and statistically accurate, as well as pedagogically sound.

In addition to his numerous research publications, Dr. Weiss is the author of A Course in Probability (Addison-Wesley, 2006). He has also authored or coauthored books in finite mathematics, statistics, and real analysis, and is currently working on a new book on applied regression analysis and the analysis of variance. His texts—well known for their precision, readability, and pedagogical excellence—are used worldwide.

Dr. Weiss is a pioneer of the integration of statistical software into textbooks and the classroom, first providing such integration in the book Introductory Statistics (Addison-Wesley, 1982). Weiss and Addison-Wesley continue that pioneering spirit to this day with the inclusion of some of the most comprehensive Web sites in the field.

In his spare time, Dr. Weiss enjoys walking, studying and practicing meditation, and playing hold ’em poker. He is married and has two sons.

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