by Julian L. Simon

Second Edition published October 1997

This text grew out of chapters in the 1969 edition of *Basic Research Methods in Social Science* by the same author, and contains the first published example of what was later called the bootstrap. Simon is best known for his research in demography, population and the economics of natural resources, and gained fame when the noted biologist Paul Ehrlich selected five commodities and bet Simon that scarcity would drive their prices up over the period of the bet (in fact, their prices all dropped). *Resampling: The New Statistics* contains a number of examples in Resampling Stats, a computer program originated by Simon, but can be read on its own without the program.

**Table of Contents**

Preface-A Look Back and A Look Ahead

Introduction-Uses Of Probability and Statistics

Afternote 1

Afternote 2

Chap 1-The Resampling Method of Solving Problems

Chap 2-Basic Concepts in Probability and Statistics

Chap 3-Basic Concepts in Probability and Statistics

Chap 4-Probability Theory

Chap 5-Probability Theory continued

Chap 6-Probability Theory Part 2, Compound Probability

Chap 7-Probability Theory, Part 3

Chap 8-Probability Theory, Part 4, Estimating Probabilities from Finite Universes:

Chap 9-On Variability in Sampling

Chap 10-The Procedures of Monte Carlo Simulation (and Resampling)

Chap 11-The Basic Ideas in Statistical Inference

Chap 12-Introduction to Statistical Inference

Chap 13-Point Estimation

Chap 14-Framing Statistical Questions

Chap 15-Hypothesis-Testing with Counted Data, Part 1

Chap 16-The Concept of Statistical Significance in Testing Hypotheses

Chap 17-The Statistics of Hypothesis-Testing With Counted Data, Part 2

Chap 18-The Statistics of Hypothesis-Testing With Measured Data

Chap 19-General Procedures for Testing Hypotheses

Chap 20-Confidence Intervals, Part 1, Assessing the Accuracy of Samples

Chap 21-Confidence Intervals, Part 2, The Two Approaches to Estimating Confidence Intervals

Chap 22-And Some Last Words About the Reliability of Sample Averages

Chap 23-Correlation and Causation

Chap 24-How Big a Sample

Chap 25-Bayesian Analysis by Simulation

Exercise Solutions

Acknowledgments

References

Tech Note