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