Modern Mathematical Statistics

by Edward J. Dudewicz (Syracuse Univ.); Satya N. Mishra (Univ. of South Alabama)

• ISBN13: 9780471814726
• ISBN10: 0471814725
• Edition: 1
• Format: Hardcover
• Copyright: 1988-01-01
• Publisher: Wiley

Summary

This modern treatment of mathematical statistics is concise, yet detailed enough to give readers a solid foundation in all aspects of the field. Treatment of each topic is thorough enough to make the coverage self-contained for a course in probability, and exceptional care has been taken to balance theory with applications. In addition to classical probability theory, such modern topics as order statistics and limiting distributions are discussed, along with applied examples from a wide variety of fields. Discussions include the core mathematical statistics topics of estimation, testing, and confidence intervals; ranking and selection procedures; decision theory; nonparametric statistics; regression and ANOVA; and robust statistical procedures. Computer-assisted data analysis is discussed at several points, reflecting the importance of statistical computation to the field. FORTRAN programs and BMDP routines are included, as well as the highly popular SAS routines. Also looks at the potential contribution of expert systems to statistics.

Table of Contents

Naive Set Theory.

Probability.

Random Variables: Discrete Case.

Random Variables: Continuous and Mixed Cases.

Moments.

Sums of Random Variables, Probability Inequalities, and Limit Laws.

Point Estimation.

Data Reduction and Best Estimation (Sufficiency, Completeness, and UMVUE's).

Tests of Hypotheses.

Interval Estimation.

Ranking and Selection Procedures.

Decision Theory.

Nonparametric Statistical Inference.

Regression and Linear Statistical Inference; Analysis of Variance.

Robust Statistical Procedures.

Statistical Tables.

Index