Statistical Methods by Rudolf J. FreundStatistical Methods by Rudolf J. Freund

Statistical Methods

byRudolf J. Freund, Rudolf J. Freund, Donna Mohr...

Other | August 17, 2010

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Statistical Methods, Third Edition, 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 that emphasizes 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. Students are required to be familiar with algebra. This updated edition includes new 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.

  • Integrates the classical conceptual approach with modern day computerized data manipulation and computer applications
  • Accessibile to students who may not have a background in probability or calculus
  • Offers reader-friendly exposition, without sacrificing statistical rigor
  • Includes many new data sets in various applied fields such as Psychology, Education, Biostatistics, Agriculture, Economics
Title:Statistical MethodsFormat:OtherDimensions:824 pages, 1 × 1 × 1 inPublished:August 17, 2010Publisher:Elsevier ScienceLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0080961037

ISBN - 13:9780080961033

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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