| Contents Notes |
Ch. 1. The Chi-squared Test of Pearson -- Ch. 2. The Chi-squared Test for a Composite Hypothesis -- Ch. 3. The Chi-squared Test for an Exponential Family of Distributions -- Ch. 4. Some Additional Examples -- Appendix: Multivariate Normal and Chi-squared Distributions: Some Definitions and Basic Properties. Chi-squared testing is one of the most commonly applied statistical techniques. It provides reliable answers for researchers in a wide range of fields, including engineering, manufacturing, finance, agriculture, and medicine. A Guide to Chi-Squared Testing brings readers up to date on recent innovations and important material previously published only in the former Soviet Union. Its clear, concise treatment and practical advice make this an ideal reference for all researchers and consultants. Authors Priscilla E. Greenwood and Mikhail S. Nikulin demonstrate the application of these general purpose tests in a wide variety of specific settings. They also detail the various decisions to be made when applying Chi-squared tests to real data, and the proper application of these tests in standard hypothesis-testing situations; describe how Chi-squared type tests allow statisticians to construct a test statistic whose distribution is asymptotically Chi-squared, and to compute power against various alternatives; devote half of the book to examples of Chi-squared tests that can be easily adapted to situations not covered in the book; provide a self-contained, accessible treatment of the mathematical requisites; and include an extensive bibliography and suggestions for further reading. |
