A reader-friendly approach to statistics in social work practice.
Statistics for Social Workers, 9/e familiarizes students with statistical tests and analyses that are most likely to be encountered by social work researchers and practitioners. This reader-friendly title emphasizes the conceptual underpinning of statistical analyses, keeping mathematics and complicated formulae to a minimum. Readers require no prior knowledge of statistics and only basic mathematical competence.
Table of Contents:
In this Section:
I) Brief Table of Contents
II) Detailed Table of Contents
I) Brief Table of Contents
Chapter 1. Introduction
Chapter 2. Frequency Distributions and Graphs
Chapter 3. Measures of Central Tendency and Variability
Chapter 4. Normal Distributions
Chapter 5. Testing Hypotheses
Chapter 6. Sampling Distributions
Chapter 7. t Tests and Analysis of Variance
Chapter 8. The Chi-Square Test of Association between Variables
Chapter 9. Correlation
Chapter 10. Regression
Chapter 11. Other Ways That Statistical Analyses Contribute to Evidence-Based Practice
II) Detailed Table of Contents
Chapter 1. Introduction
Useful Terms You Will Need to Know
Measurement iSSUES
Additional Measurement Classifications
Research Hypotheses
Classification of Variables and Their Relationship
Categories of Statistical Analyses
Statistics and data collection
Research designs and statistics
Chapter 2. Frequency Distributions and Graphs
Frequency Distributions
Grouped Frequency Distributions
Using Frequency Distributions to Analyze Data
Misrepresentation of Data
Graphs
A Caution: Computer-generated graphs
Chapter 3. Measures of Central Tendency and Variability
Measures of Central Tendency
Measures of Variability
Other Uses for Central Tendency and Variability
Chapter 4. Normal Distributions
Skewness
Kurtosis
The Normal Curve
The Standard Normal Distribution
Converting Raw Scores to z Scores and Percentiles
Deriving raw Scores From Percentiles
Chapter 5. Testing Hypotheses
Alternative Explanations for Relationships Within Samples
Probability and Inference
Refuting Sampling Error
Statistical Significance
Testing the Null Hypothesis
Errors in Drawing Conclusions About Relationships
Statistically Significant Relationships and Meaningful Findings
The Hypothesis Testing process
Chapter 6. Sampling Distributions
Sample Size and Sampling Error
What are Sampling Distribution?
Rejection Regions and hypothesis testing
Estimating Parameters
Selecting Statistical Tests
Deciding Which Test to use
Chapter 7. t Tests and Analysis of Variance
The use of t Tests
The One-sample t Test
The Dependent t Test
The Independent tTest
Misuse of t tests
Simple Analysis of Variance (Simple Anova)
Multivariate Analysis of Variance
Chapter 8. The Chi-Square Test of Association between Variables
When Chi-Square is Appropriate
Cross-Tabulation Tables
Using Chi-Square
When Chi-square is not appropriate
Using chi-square in social work practice
Cross-Tabulation With Three or More Variables
Special Applications of The Chi-Square Formula
Chapter 9. Correlation
Uses of Correlation
Scattergrams
Nonperfect Correlations
Interpreting Linear Correlations
Using Correlation for inference
Pearson’S r
Nonparametric Alternatives to Pearson’S r
Correlation With Three or More Variables
Other Multivariate analyses That use Correlation
Chapter 10. Regression
Prediction and Evidence-Based Practice
Prediction and Statistical Analysis
What is Simple Linear Regression?
Computation of the Regression Equation
More About the Regression Line
Interpreting Results
Using regression in social work practice
When is regression analysis appropriate
Regression With Three or More Variables
Other Types of Regression Analyses
Chapter 11. Other Ways That Statistical Analyses Contribute to Evidence-Based Practice
Meta-analyses
Program evaluations
Single-System designs
About the Author :
Robert W. Weinbach, Ph.D., MSW, ACSW is Distinguished Professor Emeritus at the University of South Carolina, where he continues to teach graduate level research courses in the College of Social Work. He is also a co-author of Research Methods for Social Workers, seventh Edition; The Social Worker as Manager, Sixth Edition; and is the author of Evaluating Social Work Services and Programs, (all published by Allyn & Bacon), as well as over 75 other publications and invited book chapters. He earned graduate degrees in social work from SUNY-Buffalo and Ohio State University and has worked in both medical and psychiatric social work practice and as a program evaluator.
Richard M. Grinnell, Jr. is a Professor of Social Work and holds the Clair and Clarice Platt Jones/Helen Frays Endowed Chair of Social Work Research in the School of Social Work at Western Michigan University. He received his Ph.D. in social work from the University of Wisconsin at Madison and for over the past 40 years has held academic and senior university administrative appointments in Australia, Canada, and the United States. He has published over 100 journal articles, book chapters, and conference presentations, and 36 books. His two latest books are Evaluation for Social Workers: Foundations of Evidence–Based Programs, 6th edition (Oxford University Press, 2012, with Peter Gabor and Yvonne Unrau) and Social Work Research and Evaluation: Foundations of Evidence-Based Practice, 10th edition (Oxford University Press, 2014, with Yvonne Unrau).
