[内容简介]
Data Analysis with SPSS is designed to teach students how to explore data in a systematic manner using the most popular professional social statistics program on the market today. Written in ten manageable chapters, this book first introduces students to the approach researchers use to frame research questions and the logic of establishing causal relations. Students are then oriented to the SPSS program and how to examine data sets. Subsequent chapters guide them through univariate analysis, bivariate analysis, graphic analysis, and multivariate analysis. Students conclude their course by learning how to write a research report and by engaging in their own research project. Each book is packaged with a disk containing the GSS (General Social Survey) file and the States data files. The GSS file contains 100 variables generated from interviews with 2,900 people, concerning their behaviors and attitudes on a wide variety of issues such as abortion, religion, prejudice, sexuality, and politics. The States data allows comparison of all 50 states with 400 variables indicating issues such as unemployment, environment, criminality, population, and education.Students will ultimately use these data to conduct their own independent research project with SPSS.

[目次]
Each chapter begins with "Overview" and concludes with "Summary," "Key Terms," "References and Further Reading," and "Exercises."

1、Key Concepts in Social Science Research

Empiricism and Social Science Research

Data

Developing Research Questions

Theory and Hypothesis

Relationships and Causality

2、Getting Started: Accessing, Examining, and Saving Data

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

Managing Variable Names and Labels

3、Univariate Analysis: Descriptive Statistics

Why Do Researchers Perform Univariate Analysis?

Exploring Distributions of Numerical Variables

Exploring Distributions of Categorical Variables

4、Constructing Variables

Why Construct New Variables?

Recoding Existing Variables

Computing New Variables

Recording and Running Computations Using Syntax

Using Compute to Construct an Index with Syntax

5、Assessing Association through Bivariate Analysis

Why Do We Need Significance Tests?

Analyzing Bivariate Relationships Between Two Categorical Variables

Analyzing Bivariate Relationships Between Two Numerical Variables

6、Comparing Groups through Bivariate Analysis

One-Way Analysis of Variance

Graphing the Results of an ANOVA

Post-Hoc Tests

Assumptions of ANOVA

t Tests

7、Multivariate Analysis with Linear Regression

What Are the Advantages of Multivariate Analysis?

When Can I Do a Linear Regression?

Linear Regression: A Bivariate Example

Interpreting Linear Regression Coefficients

Interpreting the R-Square Statistic

Using Linear Regression Coefficients to Make Predictions

Using Coefficients to Graph Bivariate Regression Lines

Multiple Linear Regression

Other Concerns of Linear Regression

8、Multivariate Analysis with Logistic Regression

What Is Logistic Regression?

What Are the Advantages of Logistic Regression?

When Can I Do a Logistic Regression?

Understanding the Relationships through Probabilities

Logistic Regression: A Bivariate Example

Multivariate Logistic Regression: An Example

9、Writing a Research Report

Writing Style and Audience

The Structure of a Report

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: Your Topic

Appendix 1: STATES.SAV Descriptives

Appendix 2: GSS98.SAV File Information

Appendix 3: Variable Label Abbreviations

Permissions

Index.