Statistical Methods

By

  • Rudolf Freund, Texas A&M University, U.S.A.
  • Donna Mohr
  • William Wilson, University of North Florida, Jacksonville, Florida, U.S.A.

Statistical Methods, 3e 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 intepreting 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:

  • 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
  • NEW case studies for gathering, summarizing, and analyzing data

Supplements:

  • NEW companion website with downloadable data sets and additional resources including live links to statistical software such as SAS and SPSS
  • Student Solutions Manual - to come
  • Instructor Manual - to come
  • Sample chapter - http://www.elsevierdirect.com/product.jsp?isbn=9780123749703

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Audience

Advanced undergraduates majoring or minoring in statistics, math or graduate students in an applied field requiring statistical methods: psychology, public administration, economics, sociology, education, public health, engineering, agriculture.

 

Book information

  • Published: July 2010
  • Imprint: ACADEMIC PRESS
  • ISBN: 978-0-12-374970-3


Table of 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