Statistics for Research

A survey of the most commonly used techniques of statistical analysis, written specifically for researchers who want to know how to carry out a procedure and how to interpret the results. No previous background in mathematical statistics is required.

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Statistics for Experimenters An Introduction to Design, Data Analysis, and Model Building George E. P. Box, William G. Hunter, and J. Stuart Hunter "The authors are to be congratulated for having written an excellent book. The writing is literate, and the technical aspects impeccable." - Journal of Quality Technology Demonstrates the design of highly efficient statistical and engineering programs using a special applied approach. Covers hypothesis tests, confidence intervals, comparison of means, t tests, and more. Includes many examples, illustrations, and exercises (with answers) throughout. Advanced topics of special interest are detailed in readily understood language. 1978 (0 471-09315-7) 653 pp. Computer-Intensive Methods for Testing Hypotheses An Introduction Eric W. Noreen Designed to provide a basic understanding of computer-intensive methods and their widespread applications, this book offers computer-intensive alternatives to virtually every conventional parametric and nonparametric test. Assuming no more than a working knowledge of BASIC, PASCAL or FORTRAN, this work explores how computer-intensive methods can be easily incorporated into your work.
The short, simple, and extremely flexible programs discussed here may be used as templates with only minor modification. 1989 (0 471-61136-0) 229 pp. Categorical Data Analysis Alan Agresti Chronicling the historical development of methods for analyzing categorical data, this text enables practicing statisticians to catch up with recent advances and to perform analyses. There is a strong emphasis on statistical computer packages such as SAS, SPPS, BMDP, and GLIM. Modern methods for ordinal data, longitudinal data, and generalized linear models are explained, and more than 40 examples of analyses of real data sets are offered. Coverage includes: models for categorical (or continuous) responses as special cases of generalized linear models; methods for repeated measurement data; outlined derivations of basic asymptotic and fixed-sample-size inferences; discussion of exact small-sample procedures; and prescriptions for treating ordinal variables differently than nominal variables. 1990 (0 471-85301-1) 558 pp.