For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science.

This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance between theory and methodology. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. This revision focuses on improved clarity and deeper understanding.

Table of Contents

1 Introduction to Statistics and Data Analysis

2 Probability

3 Random Variables and Probability Distributions

4 Mathematical Expectation

5 Some Discrete Probability Distributions

6 Some Continuous Probability Distributions

7 Functions of Random Variables (Optional)

8 Fundamental Sampling Distributions and Data Descriptions

9 One- and Two-Sample Estimation Problems

10 One- and Two-Sample Tests of Hypotheses

11 Simple Linear Regression and Correlation

12 Multiple Linear Regression and Certain Nonlinear Regression Models

13 One-Factor Experiments: General

14 Factorial Experiments (Two or More Factors)

15 2k Factorial Experiments and Fractions

16 Nonparametric Statistics

17 Statistical Quality Control

18 Bayesian Statistics

Bibliography

Appendix A: Statistical Tables and Proofs

Appendix B: Answers to Odd-Numbered Non-Review Exercises