Statistics using IBM SPSS : an integrative approach

著者

書誌事項

Statistics using IBM SPSS : an integrative approach

Sharon Lawner Weinberg, Sarah Knapp Abramowitz

Cambridge University Press, 2015

3rd ed

  • : pbk

大学図書館所蔵 件 / 全3件

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注記

Previous ed.: Statistics using SPSS : an integrative approach / Sharon L. Weinberg, Sarah Knapp Abramowitz (Cambridge University Press, 2008)

Includes bibliographical references (p. 588-591) and index

内容説明・目次

内容説明

Written in a clear and lively tone, Statistics Using IBM SPSS provides a data-centric approach to statistics with integrated SPSS (version 22) commands, ensuring that students gain both a deep conceptual understanding of statistics and practical facility with the leading statistical software package. With one hundred worked examples, the textbook guides students through statistical practice using real data and avoids complicated mathematics. Numerous end-of-chapter exercises allow students to apply and test their understanding of chapter topics, with detailed answers available online. The third edition has been updated throughout and includes a new chapter on research design, new topics (including weighted mean, resampling with the bootstrap, the role of the syntax file in workflow management, and regression to the mean) and new examples and exercises. Student learning is supported by a rich suite of online resources, including answers to end-of-chapter exercises, real data sets, PowerPoint slides, and a test bank.

目次

  • 1. Introduction
  • 2. Examining univariate distributions
  • 3. Measures of location, spread, and skewness
  • 4. Re-expressing variables
  • 5. Exploring relationships between two variables
  • 6. Simple linear regression
  • 7. Probability fundamentals
  • 8. Theoretical probability models
  • 9. The role of sampling in inferential statistics
  • 10. Inferences involving the mean of a single population when is known
  • 11. Inferences involving the mean when is not known: one- and two-sample designs
  • 12. Research design: introduction and overview
  • 13. One-way analysis of variance
  • 14. Two-way analysis of variance
  • 15. Correlation and simple regression as inferential techniques
  • 16. An introduction to multiple regression
  • 17. Nonparametric methods.

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