Statistics for Research, 2nd Edition

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9780471857037: Statistics for Research, 2nd Edition

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.

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From the Inside Flap:

Praise for the first edition... "Overall, I found this book to be carefully thought-out and attractive. I believe it will satisfy the objective that the authors have set; namely, to give beginning graduate students a good idea of the necessity for statistics in their research. It provides many of the tools they will need." —Journal of Quality Technology "This book meets its stated goals and is readable. I find the use of examples to teach the material to be successful in maintaining the interest level of the reader and would recommend use of the text at the introductory level." —American Scientist Statistics for Research, Second Edition presents the most commonly used statistical techniques in a clear, readable way which can be understood by someone with no previous statistical experience. This survey is written from the viewpoint of the researcher who wants to know how to carry out a procedure, how to interpret the results (whether the analysis is performed by hand or a statistical computer package), and who wants some intuitive understanding of why the procedure works. All procedures are explained in the context of realistic research situations and then summarized in general terms. The usefulness of statistics is illustrated throughout, beginning in the first chapter with inference. Probability and descriptive statistics are developed in the book as needed and do not appear as separate chapters as in most books. Interpretation of the computer output of statistical analyses and nonparametric procedures are integrated with the discussion of each statistical procedure. After a statistical procedure is explained and demonstrated, wherever it is practical to do so, the procedure is followed by demonstrations of how the SAS System is used for computer analysis of the same data. Similarly, each statistical process is followed by a nonparametrical analog to the procedure which has been under discussion. This revised edition has been expanded and contains numerous exercises after each section, over 90 figures, program statements and computer output for the SAS System, bibliographies at the end of chapters, summaries of procedures, review exercises, answers to selected exercises and all review exercises, and 19 statistical tables.

From the Back Cover:

Praise for the Second Edition

"Statistics for Research has other fine qualities besides superior organization. The examples and the statistical methods are laid out with unusual clarity by the simple device of using special formats for each. The book was written with great care and is extremely user-friendly."—The UMAP Journal

Although the goals and procedures of statistical research have changed little since the Second Edition of Statistics for Research was published, the almost universal availability of personal computers and statistical computing application packages have made it possible for today's statisticians to do more in less time than ever before.

The Third Edition of this bestselling text reflects how the changes in the computing environment have transformed the way statistical analyses are performed today. Based on extensive input from university statistics departments throughout the country, the authors have made several important and timely revisions, including:

  • Additional material on probability appears early in the text
  • New sections on odds ratios, ratio and difference estimations, repeated measure analysis, and logistic regression
  • New examples and exercises, many from the field of the health sciences
  • Printouts of computer analyses on all complex procedures
  • An accompanying Web site illustrating how to use SAS® and JMP® for all procedures

The text features the most commonly used statistical techniques for the analysis of research data. As in the earlier editions, emphasis is placed on how to select the proper statistical procedure and how to interpret results. Whenever possible, to avoid using the computer as a "black box" that performs a mysterious process on the data, actual computational procedures are also given.

A must for scientists who analyze data, professionals and researchers who need a self-teaching text, and graduate students in statistical methods, Statistics for Research, Third Edition brings the methodology up to date in a very practical and accessible way.

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