Social statistics : the basics and beyond

著者

    • Linneman, Thomas John

書誌事項

Social statistics : the basics and beyond

Thomas J. Linneman

(Contemporary sociological perspectives)

Routledge, 2011

  • : hbk

大学図書館所蔵 件 / 4

この図書・雑誌をさがす

注記

Includes bibliographical references (p. [532]) and index

内容説明・目次

内容説明

With just the right level of detail, and a graphically innovative approach, this book carefully guides students through the statistical techniques they will encounter in the real world. The basics are covered in a non-intimidating way for your students, plus multiple regression, interaction effects, logistic regression, non-linear effects. The book uses three datasets throughout: General Social Survey, American National Election Studies, World Values Survey, and includes SPSS demonstrations at the end of each chapter. Most of your students will likely take only one stats course and use only one stats book in their college careers. This one innovatively equips them for their worlds ahead, regardless of the career paths they follow.

目次

Part 1: The Basics 1. Data: What They Are and What We Do With Them 2. Telling Visual Stories: Tables and Graphs 3. The Center and What Surrounds It: Measures of Central Tendency and Variation 4. Speaking Beyond the Sample with Crosstabs: The Chi-Square Test 5. Speaking Beyond the Sample with a Mean or Proportion: Confidence Intervals 6. Speaking Beyond the Sample with More Than One Mean: T-Tests and ANOVA 7. Ratio-Level Relationships: Bivariate Correlation and Regression 8. Speaking Beyond the Sample with Slopes: Inference and Regression Part 2: Beyond the Basics 9. Dichotomies as Independent Variables: Reference Grouping 10. The Logic and Power of Controlling: Nested Regression Models 11. Comparing and Contrasting Regression Slopes: Beta Coefficients 12. Catching Up or Falling Behind: Interaction Effects 13. Predicting Probabilities Instead of Values: Logistic Regression 14. Telling Visual Stories with Regression: Path Analysis 15. Questioning the Greatness of Straightness: Nonlinear Relationships

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