ISBN-10:
0205019676
ISBN-13:
9780205019670
Pub. Date:
01/10/2011
Publisher:
Pearson
Data Analysis with SPSS: A First Course in Applied Statistics / Edition 4

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

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Product Details

ISBN-13: 9780205019670
Publisher: Pearson
Publication date: 01/10/2011
Edition description: New Edition
Pages: 288
Sales rank: 218,429
Product dimensions: 8.40(w) x 10.80(h) x 0.80(d)

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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