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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.
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 t_{α}
V. Values of χ_{α} ^{2}
VI. Values of F_{α}
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