authors:- Sweet, Stephen A.
- Grace-Martin, Karen.
subjects:- Social sciences -- Statistical methods -- Computer programs
- Mathematical statistics -- Data processing
publishers:ISBN:- 0205483879 (pbk.) :
- 9780205483877 (pbk.)
description:notes:- Previous ed.: 2002.
- Accompanied by CD-ROM in pocket.
- Includes bibliographical references (p. 267-269) and index.
- Each chapter begins with "Overview" and concludes with "Summary," "Key Terms", and "Exercises." Brief Table of Contents: Preface Acknowledgements x About the Authors x Dedication Chapter 1 * Key Concepts in Social Science Research Why Do We Need Statistics Framing Topics Into Research Questions Theory and Hypothesis Population and Samples Relationships and Causality Data Chapter 2 * Getting Started: Accessing, Examining,and Saving Data Initial Settings The Layout of SPSS Types of Variables Defining and Saving a New Data Set Managing Data Sets: Dropping and Adding Variables Merging and Importing Files Loading and Examining an Existing File Chapter 3 * Univariate Analysis: Descriptive Statistics Why Do Researchers Perform Univariate Analysis? Exploring Distributions of Scale Variables Exploring Distributions of Categorical Variables Chapter 4 * Constructing Variables Why Construct New Variables? Recoding Existing Variables Computing New Variables Recording Computations Using Syntax Chapter 5 * Assessing Association through Bivariate Analysis Why Do We Need Significance Tests? Cross Tabulations Bar Charts Correlations Scatter Plots Chapter 6 * Comparing Groups through Bivariate Analysis One-Way Analysis of Variance Post-hoc Tests Assumptions of ANOVA Graphing the Results of ANOVA T tests Chapter 7 * Multivariate Analysis with Linear Regression The Advantages of Multivariate Analysis Linear Regression: A Bivariate Example Multiple Linear Regression Other Concerns In Applying Linear Regression Assumptions of Regression Dummy Variables Outliers Causality Chapter 8 * Multivariate Analysis with Logistic Regression What Is Logistic Regression? When Can I Do a Logistic Regression? Understanding the Relationships through Probabilities Logistic Regression: A Bivariate Example Multivariate Logistic Regression: An Example Interpreting Logistic Regression Output Using Multivariate Logistic Regression Coefficients to Make Predictions Using Multivariate Coefficients to Graph a Logistic Regression Line Chapter 9 * Writing a Research Report Overview Writing Style and Audience The Structure of a Report References and Further Reading Chapter 10 * Research Projects Potential Research Projects Research Project 1: Racism Research Project 2: Suicide Research Project 3: Criminality Research Project 4: Welfare Research Project 5: Sexual Behavior Research Project 6: Education Research Project 7: Health Research Project 8: Happiness Research Project 9: Your Topic Appendix 1: STATES.SAV Descriptives Appendix 2: GSS98.SAV File Information Appendix 3: Variable Label Abbreviations Permissions Index
people who borrowed this, also borrowed:
University of Huddersfield Library Catalogue