Summary

This book provides the basic methods of introductory statistics, focusing on real-life examples from medicine, public health, and the natural sciences. Probability, hypothesis testing, estimation, analysis of contingency tables, regression analysis, and analysis of variance are presented in a nonmathematical format and provide a basis for understanding statistics. This foundation is expanded to include such important topics in biomedical statistics as design and implementation of clinical trials, statistical evaluation of diagnostic tests, methods of randomization, and methods of analyzing survival data with incomplete observations.

Author Biography

BYRON WILLIAM BROWN JR., PhD, was a professor in and former chair of the Department of Health Policy and Research at Stanford University. For over 30 years, he made significant contributions to the university's research and teachings on various areas of study such as cancer treatment and the design of clinical trials. Dr. Brown is now deceased.

MYLES HOLLANDER, PhD, is Robert O. Lawton Distinguished Professor of Statistics at Florida State University in Tallahassee. He served as editor of the Theory and Methods Section of the Journal of the American Statistical Association from 1993-96.

CHAPTER 1: Introduction 1

CHAPTER 2: Elementary Rules of Probability 13

CHAPTER 3: Populations, Samples, and the Distribution of the Sample Mean 37

1. Populations and Distributions 38

2. Sampling from Finite Populations 64

3. The Distribution of the Sample Mean 72

CHAPTER 4: Analysis of Matched Pairs Using Sample Means 85

1. A Confidence Interval for the Treatment Effect 86

2. A Hypothesis Test for the Treatment Effect 96

3. Determining the Sample Size 102

CHAPTER 5: Analysis of the Two-Sample Location Problem Using Sample Means 109

1. A Confidence Interval for the Difference Between the Population Means 110

2. A Hypothesis Test for the Difference Between the Population Means 116

3. Determining Sample Sizes 119

4. Testing the Assumption of Equal Population Variances 122

CHAPTER 6: Surveys and Experiments in Medical Research 131

Application of Statistics in Laboratory and Clinical Studies 131

Randomized Clinical Experiments 134

Ethics and Statistical Aspects of the Clinical Trial 137

Retrospective Studies, Prospective Studies, and Randomized Clinical Experiments 140

CHAPTER 7: Statistical Inference for Dichotomous Variables 149

A Confidence Interval for a Success Probability p 150

Hypothesis Tests for a Success Probability p 156

CHAPTER 8: Comparing Two Success Probabilities 173

A Confidence Interval for the Difference Between the Success Probabilities 174

A Hypothesis Test for the Difference Between the Success probabilities 178

CHAPTER 9: Chi-Squared Tests 195

The Chi-Squared Test for k Probabilities (Goodness of Fit) 196

r x k Tables: Chi-Squared Tests of Homogeneity and Independence 201

A Test for Trend in Proportions 211

CHAPTER 10: Analysis of & Sample Problems 225

The Completely Randomized Experiment 226

The Randomized Blocks Experiment 241

CHAPTER 11: Linear Regression and Correlation 261

1. Linear Regression 262

2. Correlation 281

3. Rank Correlation 292

CHAPTER 12: Analysis of Matched Pairs Using Ranks 309

1. The Wilcoxon Signed Rank Test 310

2. A Nonparametric Confidence Interval Based on the Signed Rank Test 317

CHAPTER 13: Analysis of the Two-Sample Location Problem Using Ranks 327

1. The Wilcoxon Two-Sample Rank Sum Test 328

2. A Nonparametric Confidence Interval Based on the Rank Sum Test 333

CHAPTER 14: Methods for Censored Data 341

APPENDIX A: Glossary 361

APPENDIX B: Answers to Selected Questions and Solutions to Selected Problems 375

APPENDIX C: Mathematical and Statistical Tables 407

INDEX 451

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