Synopses & Reviews
This brief course in statistical inference was extensively class tested by the author at the University of Illinois, and it requires only a basic familiarity with probability and matrix and linear algebra. Ninety problems with solutions make it an ideal choice for self-study as well as a helpful review of a wide range of statistical formulas with applications in business, government, public administration, and other fields.
The first eight chapters review results from basic probability that are important to statistics, including transformation of random variables, Jacobians, moment-generating functions, sampling from a normal population, order statistics, and the central limit theorem. Additional subjects include estimation, confidence intervals, hypothesis testing, correlation, nonparametric statistics, and many other topics.
Synopsis
This book offers a brief course in statistical inference that requires only a basic familiarity with probability and matrix and linear algebra. Ninety problems with solutions make it an ideal choice for self-study. 2011 edition.
Table of Contents
1. Transformation of Random Variables2. Jacobians3. Moment-generating Functions4. Sampling from a Normal Population5. The T and F Distributions6. Order Statistics7. The Weak Law of Large Numbers8. The Central Limit Theorem9. Estimation10. Confidence Intervals11. More Cofidence Intervals12. Hypothesis Testing13. Chi Square Tests14. Sufficient Statistics15. Rao-Blackwell Theorem16. Lehmann-Scheffe Theorem17. Complete Sufficient Statistics for the Exponential Class18. Bayes Estimates19. Linear Algebra Review20. Correlation21. The Multivariate Normal Distribution22. The Bivatate Normal Distribution23. Cramer-Rao Inequality24. Nonparametric Statistics25. The Wilcoxon TestSolutions to ProblemsIndex