Data Analysis with SPSS A First Course in Applied Statistics
by Sweet, Stephen A.; Grace-Martin, Karen A.Edition: 4th
Format: Paperback w/Disk
Pub. Date: 2010-12-27
Publisher(s): Pearson
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Summary
Data Analysis with SPSSis 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.
Table of Contents
TABLE OF CONTENTS:
1. BRIEF
2. COMPREHENSIVE
BRIEF 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
COMPREHENSIVE TABLE OF CONTENTS
C hapter 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
Dropping and Adding Variables
Merging and Importing Files
Loading and Examining an Existing File
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
Research Project 9: Your Topic
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