Data Analysis with SPSS: A First Course in Applied Statistics / Edition 4

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More About This Textbook


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.

Note: MySearchLab does not come automatically packaged with this text. To purchase MySearchLab, please visit: or you can purchase a ValuePack of the text + MySearchLab with Pearson eText (at no additional cost). ValuePack ISBN-10: 0205863728 / ValuePack ISBN-13: 9780205863723

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Product Details

  • ISBN-13: 9780205019670
  • Publisher: Pearson
  • Publication date: 1/10/2011
  • Edition description: New Edition
  • Edition number: 4
  • Pages: 288
  • Sales rank: 214,322
  • Product dimensions: 8.40 (w) x 10.80 (h) x 0.80 (d)

Table of Contents





C hapter 1 • Key Concepts in Social Science Research

Chapter 2 • Getting Started: Accessing, Examining, and Saving

Chapter 3 • Univariate Analysis: Descriptive Statistics

Chapter 4 • Constructing Variables

Chapter 5 • Assessing Association through Bivariate Analysis

Chapter 6 • Comparing Group Means through Bivariate Analysis

Chapter 7 • Modeling Relationships of Multiple Variables with Linear Regression

Chapter 8 • Logistic Regression

Chapter 9 • Writing a Research Report

Chapter 10 • Research Projects


C hapter 1Key Concepts in Social Science Research


Framing Topics Into Research Questions

Theories and Hypotheses

Population and Samples

Relationships and Causality

Data Sets

Parts of a Data Set

Reliability and Validity


Key Terms


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


The Layout of SPSS

Types of Variables

Initial Settings

Defining and Saving a New Data Set

Managing Data Sets: Dropping and Adding Variables, Merging Data Sets

Dropping and Adding Variables

Merging and Importing Files

Loading and Examining an Existing File


Key Terms


Chapter 3Univariate Analysis: Descriptive Statistics


Why Do Researchers Perform Univariate Analysis?

Exploring Distributions of Scale Variables

Exploring Distributions of Categorical Variables


Key Terms


Chapter 4 • Constructing Variables


Why Construct New Variables From Existing Data?

Recoding Existing Variables

Computing New Variables

Recording Computations Using Syntax

Minimizing Missing Values in Computing New Variables


Key Terms


Chapter 5Assessing Association through Bivariate Analysis


Why Do We Need Significance Tests?

Analyzing Bivariate Relationships Between Two Categorical Variables

Analyzing Bivariate Relationships Between Two Scale Variables


Key Terms


Chapter 6Comparing Group Means through Bivariate Analysis


One-Way Analysis of Variance

Post-hoc Tests

Assumptions of ANOVA

Graphing the Results of ANOVA

T tests


Key Terms


Chapter 7Modeling Relationships of Multiple Variables with Linear Regression


The Advantages of Modeling Relationships in Multiple Regression

Linear Regression: A Bivariate Example

Multiple Linear Regression

Other Concerns In Applying Linear Regression

Building Multiple Variable Models


Key Terms


Chapter 8Logistic Regression


What Is Logistic Regression?

When Can I Use a Logistic Regression?

Understanding Relationships through Probabilities

Logistic Regression: A Bivariate Example

Multiple Variable Logistic Regression: An Example


Key Terms


Chapter 9Writing a Research Report


Writing Style and Audience

The Structure of a Report


Key Terms


Chapter 10Research Projects

Potential Research Projects

Research Project 1: Racism

Research Project 2: Suicide

Research Project 3: Criminality

Research Project 4: Welfare and Other Public Aid Consumption

Research Project 5: Sexual Behavior

Research Project 6: Education

Research Project 7: Health

Research Project 8: Happiness

Research Project 9: Your Topic

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