# Data Analysis with SPSS: A First Course in Applied Statistics, CourseSmart eTextbook, 4th Edition

Published Date: Jan 4, 2011

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## Description

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.

1. BRIEF

2. COMPREHENSIVE

Chapter 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

Chapter 1  • Key Concepts in Social Science Research

Overview

Framing Topics Into Research Questions

Theories and Hypotheses

Population and Samples

Relationships and Causality

Data Sets

Parts of a Data Set

Reliability and Validity

Summary

Key Terms

Exercises

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

Overview

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

Merging and Importing Files

Summary

Key Terms

Exercises

Chapter 3  •  Univariate Analysis: Descriptive Statistics

Overview

Why Do Researchers Perform Univariate Analysis?

Exploring Distributions of Scale Variables

Exploring Distributions of Categorical Variables

Summary

Key Terms

Exercises

Chapter 4  • Constructing Variables

Overview

Why Construct New Variables From Existing Data?

Recoding Existing Variables

Computing New Variables

Recording Computations Using Syntax

Minimizing Missing Values in Computing New Variables

Summary

Key Terms

Exercises

Chapter 5  •  Assessing Association through Bivariate Analysis

Overview

Why Do We Need Significance Tests?

Analyzing Bivariate Relationships Between Two Categorical Variables

Analyzing Bivariate Relationships Between Two Scale Variables

Summary

Key Terms

Exercises

Chapter 6  •  Comparing Group Means through Bivariate Analysis

Overview

One-Way Analysis of Variance

Post-hoc Tests

Assumptions of ANOVA

Graphing the Results of ANOVA

T tests

Summary

Key Terms

Exercises

Chapter 7  •  Modeling Relationships of Multiple Variables with Linear Regression

Overview

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

Summary

Key Terms

Exercises

Chapter 8  •  Logistic Regression

Overview

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

Summary

Key Terms

Exercises

Chapter 9  •  Writing a Research Report

Overview

Writing Style and Audience

The Structure of a Report

Summary

Key Terms

Exercises

Chapter 10  •  Research 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