Using Statistical Methods in Social Science Research: With a Complete SPSS Guide, 3rd Edition

Length: 544 pages
Edition: 3
Language: English
Publisher: Oxford University Press
Publication Date: 2021-02-12
ISBN-10: 0197522432
ISBN-13: 9780197522431
Sales Rank: #942277 (See Top 100 Books)

Using Statistical Methods in Social Science Research, Third Edition is the user-friendly text every student needs for analyzing and making sense of quantitative data. With over 20 years of experience teaching statistics, Soleman H. Abu-Bader provides an accessible, step-by-step description of the process needed to organize data, choose a test or statistical technique, analyze, interpret, and report research findings.

The book begins with an overview of research and statistical terms, followed by an explanation of basic descriptive statistics. It then focuses on the purpose, rationale, and assumptions made by each test, such as Pearson’s correlation, student’s t-tests, analysis of variances, and simple linear regression, among others. The book also provides a wealth of research examples that clearly display the applicability and function of these tests in real-world practice. In a separate appendix, the author provides a step-by-step process for calculating each test for those who still like to understand the mathematical formulas behind these processes.

Cover Page
Title Page
Copyright Page
Dedication
Contents
Preface
List of Figures
List of Tables
List of SPSS Screen Captures
1 Overview of Mathematical and Research Methodological Terms
    Learning Objectives
    Introduction
    Basic Mathematical Concepts
    Variable and Constants
    Levels of Measurement
    Research Hypotheses
    Psychometric Properties of an Instrument
    Population and Sample
    Descriptive and Inferential Statistics
    Types of Relationships between Two Variables
    Summary
    Key Terms
    Practical Exercises
2 Working with SPSS
    Learning Objectives
    Introduction
    About the SPSS Program
    Creating an Instrumentation Codebook
    Practical Example
    Starting the SPSS Program
    Summary
    Key Terms
    Practical Exercises
3 Data Organization and Summary: Frequency Tables and Graphs
    Learning Objectives
    Introduction
    Frequency Distributions
    Graphic Presentations of Data
    Summary
    Key Terms
    Practical Exercises
4 Descriptive Statistics: Measures of Central Tendency, Variability, and Percentiles
    Learning Objectives
    Introduction
    Measures of Central Tendency
    Measures of Variability
    What Measure(s) to Report
    Percentile and Percentile Ranks
    Box-and-Whisker Plot
    Summary
    Key Terms
    Practical Exercises
5 Distributions, Data Transformations, and Standard Z Scores
    Learning Objectives
    Introduction
    Normality of Distributions
    Standard Scores (Z Scores)
    Summary
    Key Terms
    Practical Exercises
6 Hypothesis Testing and Selecting a Statistical Test
    Learning Objectives
    Introduction
    Research Hypotheses
    Errors in Hypothesis Testing
    Confidence Interval
    Selecting a Statistical Test
    Summary
    Key Terms
    Practical Exercises
7 Bivariate Correlations
    Learning Objectives
    Introduction
    Correlation
    Scatterplot
    Correlation and Causality
    Correlational Tests
        Pearson’s product-moment correlation coefficient
        Point-biserial correlation coefficient
    Assumptions
    Spearman’s Rank Correlation Coefficient
    Partial Correlation Test
    Practical Examples
    Summary
    Key Terms
    Practical Exercises
8 Difference between Two Group Means: The One-Sample Case and Two-Sample Case t-Tests
    Learning Objectives
    Introduction
    Student’s t-Tests
    One-Sample Case t-Test
    Two-Sample Case t-Test
    Mann-Whitney U Test
    Practical Examples
    Summary
    Key Terms
    Practical Exercises
9 Dependent t-Test: Two-Paired Observations
    Learning Objectives
    Introduction
    Dependent t-Test
    Wilcoxon Signed Ranks Test
    Practical Examples
    Summary
    Key Terms
    Practical Exercises
10 K Group Comparisons: One-Way Analysis of Variance and Covariance
    Learning Objectives
    Introduction
    Why Not Use the Independent t-Test?
    Analysis of Variance: An Overview
    One-Way ANOVA
    One-Way ANCOVA
    Sources of Variations in ANOVA and ANCOVA
    Assumptions of ANOVA and ANCOVA
    Kruskal-Wallis H Test
    Post Hoc Tests
    Practical Examples
    Summary
    Key Terms
    Practical Exercises
11 Chi-Square Goodness-of-Fit Test and Test of Association
    Learning Objectives
    Introduction
    Chi-Square Test
    Chi-Square Goodness-of-Fit Test
    Chi-Square Test of Association
    Contingency Table
    Assumptions of Chi-Square Tests
    Fisher’s Exact Test
    Measures of Association
    Practical Examples
    Summary
    Key Terms
    Practical Exercises
12 Simple Linear Regression
    Learning Objectives
    Introduction
    Simple Linear Regression
    Regression Equations and Scatterplot
    Regression Coefficients
    Confidence Interval
    Assumptions
    Practical Example
    Summary
    Key Terms
    Practical Exercises
Appendix A: SPSS Data Files
    Data File 1: Experimental Design (N = 60)
    Data File 2: Immigrants (N = 40)
    Data File 3: Job Satisfaction (N = 218)
    Data File 4: Mental Health (N = 155)
    Data File 5: Refugees (N = 230)
    Data File 6: Reliability Analysis (N = 110)
    Data File 7: Senior Citizens (N = 90)
    Data File 8: Well-Being (N = 182)
Appendix B: Hand Calculations
    B.1. Correlational Tests
    B.2. One-Sample Case and Two-Sample Case T-Tests
    B.3. Student’s T-Test—Two-Paired Observations
    B.4. One-Way Analysis of Variance and Covariance
    B.5. Chi-Square Tests
    B.6. Simple Linear Regression
Appendix C: Critical Values
    Table C.1. Z Scores
    Table C.2. Pearson’s Correlation
    Table C.3. Spearman’s Correlation
    Table C.4. T Distribution
    Table C.5. Wilcoxon Signed Ranks Test
    Table C.6. F Distribution
    Table C.7. Mann-Whitney U Test
    Table C.8. Tukey HSD Q Test
    Table C.9. Chi-Square
References
Index