Skip to main content Accessibility help
Internet Explorer 11 is being discontinued by Microsoft in August 2021. If you have difficulties viewing the site on Internet Explorer 11 we recommend using a different browser such as Microsoft Edge, Google Chrome, Apple Safari or Mozilla Firefox.

Statistics for the Social Sciences A General Linear Model Approach

Authors

, Utah Valley University
Published 2020

Description

The second edition of Statistics for the Social Sciences prepares students from a wide range of disciplines to interpret and learn the statistical methods critical to their field of study. By using the General Linear Model (GLM), the author builds a foundation that enables students to see how statistical methods are interrelated enabling them to build on the basic skills. The author makes statistics relevant to students' varying majors by using fascinating real-life examples from the social sciences. Students who…

  • Get access
  • Add bookmark
  • Cite
  • Share
Resources available Unlock the full potential of this textbook with additional resources. There are free resources and Instructor restricted resources available for this textbook. Explore resources

Key features

  • Illustrates statistical concepts and methodologies with real data drawn from the social sciences to make statistics relevant to students' interests and field of study
  • Includes step-by-step instructions with screenshots to show readers how to conduct and interpret each statistical analysis using Excel and SPSS
  • Clearly explains the interconnections among statistical procedures using the General Linear Model as a framework to teach students the commonalities among statistical methods
  • Emphasizes modern reporting practices and interpretation of statistics in conformity with the latest developments from the replication crisis and the Journal Article Reporting Standards from APA

About the book

Access options

Review the options below to login to check your access.

Purchase options

There are no purchase options available for this title.

Have an access code?

To redeem an access code, please log in with your personal login.

If you believe you should have access to this content, please contact your institutional librarian or consult our FAQ page for further information about accessing our content.

Also available to purchase from these educational ebook suppliers

Related content

AI generated results by Discovery for publishers [opens in a new window]