Understanding and Applying Research Design

by Abbott, Martin Lee; Mckinney, Jennifer

• ISBN13: 9781118096482
• ISBN10: 1118096487
• Edition: 1st
• Format: Hardcover
• Copyright: 2012-12-17
• Publisher: Wiley

Summary

This introductory guide provides a fresh approach to integrating design and statistics in a hands-on fashion that incorporates the power of SPSS® software to solve real-world problems. It explores the areas of design and causation-allowing readers to pose, test, and interpret research questions with live data. By integrating exercises and worksheets, the book allows readers to examine real world data from various fields of research-making it an ideal text for professionals and upper-level students involved in the social sciences.

Author Biography

MARTIN LEE ABBOTT, PhD, is Professor of Sociology at Seattle Pacific University, where he also serves as Executive Director of the Washington School Research Center. He is the author of The Program Evaluation Prism: Using Statistical Methods to Discover Patterns and Understanding Educational Statistics Using Microsoft Excel® and SPSS®, both from Wiley.

JENNIFER McKINNEY, PhD, is Associate Professor and Co-chair of the Department of Sociology and Director of the Women’s Studies Program at Seattle Pacific University. She publishes articles, makes presentations, and consults on and teaches research design.

Table of Contents

CHAPTER 1 ‘Duh’ Science vs. ‘Huh’ Science

How do we know what we know?

‘Duh’ Science

‘Huh Science’

How Does Social Research Actually Work?

EXERCISE: Should Marijuana Be Made Legal?

Terms and Concepts

CHAPTER 2 Theories and Hypotheses

What are theories?

What are Hypotheses?

Operationalizing Variables

EXERCISE: Operationalizing Concepts

Independent and Dependent Variables

Terms and Concepts

CHAPTER 3 Observation and Empirical Generalization

Quantitative Designs

Surveys

Aggregate Data

EXERCISE: Using the Religious Congregations and Membership Study (RCMS)

Experiments

Qualitative Designs

Field Research

Content Analysis

Empirical Generalizations

Correlational versus Causal Relationships

Types of Research

Terms and Concepts

CHAPTER 4 Ethics

Human Subjects Abuses

Protection of Humans in Research

Professional Ethical Standards

Terms and Concepts

CHAPTER 5 Using SPSS® In Research

Real-World data

Coverage of Statistical Procedures

SPSS® Basics

General Features

Using SPSS with GSS Data

CHAPTER 6 Chi Square and Contingency Table Analysis

Contingency Tables

Work Autonomy and Personal Health: An Example of a Contingency Table

Using Chi Square to Determine the Significance of Research Findings

Using SPSS® for the Chi Square Test of Independence

The Crosstabs Procedure

Effect Size: Contingency Coefficient

Effect Size: Phi Coefficient

Effect Size: Cramer’s V

Creating and Analyzing the Contingency Table Data Directly

Terms and Concepts

WHEEL OF SCIENCE: PROCEDURES OF RESEARCH

CHAPTER 7 Learning from Populations: Censuses and Samples

Censuses

Samples

Probability Sampling

Types of Probability Samples

Sampling and Statistics

Potential Biases in Probability Samples

Non-probability "Samples"

Exercise: Populations and Sampling

Terms and Concepts

CHAPTER 8 Measurement

Variables and Constants

Operationalization

Variation

Constants

Levels of Measurement

Exercise: Levels of Measurement

Units of Analysis

Reliability and Validity of Measures

Terms and Concepts

CHAPTER 9 Correlation

The Nature of Correlation: Explore and Predict

Different Measurement Values

Correlation Measures

Interpreting the Pearson’s Correlation

An example of Correlation

Assumptions for Correlation

Plotting the Correlation: The Scattergram

Patterns of Correlations

Creating the Scattergram

Evaluating Pearson’s r

Correlation Using SPSS®

Interpreting r: Effect Size

Correlation Influences

Correlation is Not Causation

An Example of Correlation

Non Parametric Statistics

Terms and Concepts

CHAPTER 10 Regression

Understanding Regression through Correlation

Regression Models

Using SPSS to Understand Regression

Interpreting Multiple Regression: The Combined, Omnibus, Findings

Interpreting Multiple Regression: The Individual Predictor Findings

Using MLR to Establish Causality

Using MLR with Categorical Data

Terms and Concepts

CHAPTER 11 Causation

Criteria for Causation

Using ‘Control’ Variables to Detect Spuriousness

Intervening Variables

Regression Analysis and Testing for Spuriousness

Exercise: Testing Spuriousness in Crosstabs

Exercise: Testing for Spuriousness in Regression

Terms and Concepts

WHEEL OF SCIENCE: DESIGNS OF RESEARCH

CHAPTER 12 Survey Research

Nature of The Survey

Interviews

Telephone Interviews

Questionnaires

Online Survey Methods

Online Forums

Survey Item Construction

Using Time in Survey Studies

Exercise: Survey Research in Action

Ghosts, UFOs, and Other Paranormal Beliefs

Terms and Concepts

CHAPTER 13 Aggregate Research

Nature of Aggregate Data

Areal and Social Units

Exercise: Putting It Together

Exercise: Exploring Congregations In America

Terms and Concepts

CHAPTER 14 Experiments

Experimental Designs

Pre-experimental Designs

True Experimental Designs

Quasi-Experimental Designs

Experimental settings

Ethics

Exercise: Experiments in Action

Terms and Concepts

CHAPTER 15 Statistical Methods of Difference - T Test

Independent and Dependent Samples

Independent T Test

Independent T Test: The Procedure

Independent T Test Example

Terms and Concepts

CHAPTER 16 Analysis of Variance

The Nature of the ANOVA Design

The Components of Variance

The Process of ANOVA

Calculating ANOVA

Effect Size

Post Hoc Analyses

Assumptions of ANOVA

Additional Considerations with ANOVA

A Real World Example of ANOVA

Using SPSS for ANOVA Procedures

SPSS ANOVA Results for the Example Study

SPSS Procedures with One Way ANOVA

Terms and Concepts

CHAPTER 17 Field Research

Selecting a Topic

Entering the Field

What Happens in the Field?

Reliability

Ethical Concerns

Exercise: Field Research in Action

Terms and Concepts

CHAPTER 18 Content Analysis

Defining the Population

Census or Sample?

Coding in Content Analysis

Coding Rolling Stone

Reliability and Validity

Exercise: Content Analysis of Popular Magazines

Terms and Concepts

Statistical Procedures Unit A: Writing the Statistical Research Summary

Statistical Procedures Unit B: The Nature of Inferential Statistics

Probability

Probability, the Normal Curve, and ‘P Values’

Populations (Parameters) and Samples (Statistics)

The Hypothesis Test

Inferential Statistics Terms and Concepts

Data Management Unit A: Use and Functions of SPSS

Management Functions

Additional Management Functions

Analysis Functions

Data Management Unit A: Terms and Concepts

Data Management Unit B: Using SPSS to Recode for T Test

Using SPSS to Recode Questionnaire Items

Data Management Unit B: Terms and Concepts

Data Management Unit C: Descriptive Statistics

Descriptive and Inferential Statistics

Descriptive Statistics

Descriptive Procedures for Nominal and Ordinal Data

Descriptive Procedures for Interval Data

Obtaining Descriptive (Numerical) Statistics from SPSS®

Obtaining Descriptive (Visual) Statistics from SPSS®

Data Management Unit C: Terms and Concepts

Statistical Procedures Unit C: Z Scores

The Nature of the Normal Curve

The Standard Normal Score: z score

Calculating z Scores

Using SPSS® to Create z Scores

Terms and Concepts

Glossary

Bibliography