# Statistical Methods

Textbook

By: Rudolph J Freund, William J Wilson and Donna Mohr

796 pages, Figs, tabs

Hardback | Aug 2010 | Edition: 3 | #186070 | ISBN-13: 9780123749703
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NHBS Price: £73.00 \$96/€82 approx

Statistical Methods, 3/e provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach emphasizing concepts and techniques for working out problems and interpreting results. The book includes research projects, real-world case studies, numerous examples and data exercises organized by level of difficulty. This text requires that a student be familiar with algebra.

New to this edition include the following: new expansion of exercises applying different techniques and methods; new examples and datasets using current real-world data; new text organization to create a more natural connection between regression and the Analysis of the Variance; new material on generalized linear models; new expansion of nonparametric techniques; new student research projects; and, new case studies for gathering, summarizing, and analyzing data. Supplements include the following: New companion website with downloadable data sets and additional resources including live links to statistical software such as SAS and SPSS; Student Solutions Manual; and, Instructor Manual.

This title integrates the classical conceptual approach with modern day computerized data manipulation and computer applications. It is accessible to students who may not have a background in probability or calculus. It offers reader-friendly exposition, without sacrificing statistical rigor. It includes many new data sets in various applied fields such as Psychology, Education, Biostatistics, Agriculture, and Economics.

## Contents

1. Data and statistics;
2. Probability and sampling distributions;
3. Principles of inference;
4. Inferences on a single population;
5. Inferences for two populations;
6. Inferences for two or more means;
7. Linear regression;
8. Multiple regression;
9. Linear models;
10. Factorial experiments;
11. Design of experiments;
12. Categorical data;
13. Generalized linear models;
14. Nonparametric methods

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