Data Analysis with SPSS / Edition 3

Data Analysis with SPSS / Edition 3

by Stephen A. Sweet, Karen Grace-Martin
     
 

ISBN-10: 0205483879

ISBN-13: 9780205483877

Pub. Date: 01/10/2008

Publisher: Allyn & Bacon, Inc.

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

Overview

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.

Product Details

ISBN-13:
9780205483877
Publisher:
Allyn & Bacon, Inc.
Publication date:
01/10/2008
Edition description:
REV
Pages:
224
Product dimensions:
8.50(w) x 10.82(h) x 0.61(d)

Table of Contents

Brief Table of Contents:
Chapter 1: Key Concepts in Social Science Research Chapter 2: Getting Started: Accessing, Examining, and Saving Data Chapter 3: Univariate Analysis: Descriptive Statistics Chapter 4: Constructing Variables Chapter 5: Assessing Association through Bivariate Analysis Chapter 6: Comparing Groups through Bivariate Analysis Chapter 7: Multivariate Analysis with Linear Regression Chapter 8 Multivariate Analysis with Logistic Regression Chapter 9: Writing a Research Report Chapter 10: Research Projects

Comprehensive Table of Contents:
*Each chapter begins with “Overview,” and concludes with “Summary,” “Key Terms", and “Exercises.”


Chapter1: 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

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