Statistics for Human Service Evaluation

Reginald O. York - University of North Carolina Wilmington, USA

Other Titles in:
Evaluation (General) | Evidence-based Practice | Social Work Research Methods

December 2016 | 272 pages | SAGE Publications, Inc

This practical book shows how both Excel® and SPSS® can be used for analyzing data for human service evaluation. Assuming no prior instruction for statistics, the text utilizes a “learn by doing” approach: readers see the use of statistics demonstrated and then are encouraged to apply their own data to statistical analysis with step-by-step guidance. Decision trees, practice exercises, and quizzes ensure readers will be well prepared to practice data analysis in a wide variety of human services situations.

Preface

Acknowledgments

About the Author

Chapter 1 Why Do We Use Statistics?

Why We Use Statistics

What You Will Find in the Rest of This Chapter

Two Key Issues Addressed by Data Analysis—Practical Significance and Statistical Significance

Using Statistics to Describe Clients, Evaluate Services, and Explain Client Behavior

Descriptive and Inferential Statistics

How Do We Analyze Data the User-Friendly Way?

What You Will Learn From This Book

Quiz

Key Terms

Chapter 2 Using the Computer for Statistical Analysis of Data

Using Excel for Statistical Analysis

Using SPSS for Statistical Analysis

The Structure of Excel and SPSS for Data Analysis

Using Excel in a User-Friendly Approach to Data Analysis— An Illustration

Reporting Your Findings

Summary of How to Use Excel

Quiz

Chapter 3 Selecting a Statistic to Answer Your Research Question

Finding a Descriptive Statistic

Finding a Statistic to Test Your Hypothesis in Evaluative Research

The Study Hypothesis

Things to Do Before You Seek a Statistic for an Evaluative Hypothesis

Finding Your Statistic for Testing the Evaluative Research Hypothesis: One Example

Practice Exercise

Key Terms

Chapter 4 Using Descriptive Statistics to Describe Your Study Sample

Deciding What Variables to Describe

Deciding What Statistics to Report About Your Study Subjects

Some Common Descriptive Statistics

Variance and the Normal Distribution

Using the Special Excel Files for Descriptive Statistics

Using SPSS for Descriptive Statistics

Summary

Quiz

Key Terms

Chapter 5 Analyzing Data With Pretest and Posttest Measurements of One Group

Using the t Test

Examining Statistical Significance and Practical Significance With the t Test

Testing Your Hypothesis With the Paired-Samples t Test When You Have Matching Pretest and Posttest Scores

Testing Your Hypothesis With the One-Sample t Test When You Have Pretest and Posttest Scores That Cannot Be Matched

Testing Your Hypothesis With the Binomial Test When You Have Pretest and Posttest Measurements of a Dichotomous Variable

Using the Binomial Test for the Posttest-Only Design When You Have a Threshold Proportion for Comparison

Summary

Quiz

Practice Exercise

Key Terms

Chapter 6 Analyzing Data When You Are Comparing Two Groups

Using the Independent-Samples t Test When You Are Comparing the Gain Scores of Two Groups

Using Chi Square to Compare Two Groups When You Have a Dichotomous Dependent Variable

Quiz

Practice Exercise

Key Terms

Chapter 7 Analyzing Data When You Are Evaluating a Single Client

Using the One-Sample t Test When You Have a Single Baseline Score and Several Treatment Scores

Using the Standard Deviation Approach When You Have Several Baseline Scores and Several Treatment Scores

Using Other Single-Subject Designs With Data Measured at the Interval Level

Using the Binomial Test for the AB Design When Data Are Measured as a Dichotomy

Quiz

Practice Exercise

Key Terms

Chapter 8 Explaining Client Gain

Examining the Relationship Between Client Gain and a Variable Measured at the Nominal Level

Examining the Relationship Between Client Gain and a Variable Measured at the Interval or Ordinal Level

Using Multiple Regression Analysis to Examine the Relationship Between Client Gain Scores and More Than One Other Variable

Quiz

Practice Exercise: Youth Diversion Program

Key Terms

Chapter 9 A Synopsis of Selected Statistical Tests for Examining Nominal Data

Chi Square and the Binomial Test: A Review

Examination of the Relationship Between Two Nominal Variables With Independent Data Using Chi Square, the Phi Coefficient, and the Contingency Coefficient

Examination of the Relationship Between Two Nominal Variables With Related Data Using the McNemar Test

Using the Binomial Test to Compare the Categories of a Dichotomous Variable

Key Terms

Chapter 10 A Synopsis of Selected Statistical Tests for Examining Ordinal Data

Using the Spearman Rank Correlation Coefficient When You Have Two Ordinal Variables

Using the Mann–Whitney U Test When You Have Independent Data With One Ordinal Variable and a Dichotomous Nominal Variable

Using the Wilcoxon Matched-Pairs Signed Ranks Test When You Have Related Data With a Dichotomous Variable and an Ordinal Variable

Using the Kruskal–Wallis One-Way Analysis of Variance When You Have Independent Data With an Ordinal Variable and a Nominal Variable That Has More Than Two Categories

Key Terms

Chapter 11 Statistics for Evidence-Based Practice

What Is Evidence-Based Practice?

Levels of Evidence

Statistics for Review of Evidence

Some Tips for Reviewing the Evidence

Key Terms

Answers to Quizzes and Review Questions

Appendixes

References

Index

Supplements

Companion Website

Student Study Site

Use the Student Study Site to get the most out of your course!
Our Student Study Site at study.sagepub.com/york is completely open access and offers a wide range of additional features!

The open-access Student Study Site includes the following:

Mobile-friendly eFlashcards reinforce understanding of key terms and concepts that have been outlined in the chapters.
Mobile-friendly web quizzes allow for independent assessment of progress made in learning course material.

Instructor's Manual

Instructor Teaching Site

Calling all instructors!
It’s easy to log on to SAGE’s password-protected Instructor Teaching Site at study.sagepub.com/york for complete and protected access to all text-specific Instructor Resources for Reginald O. York’s Statistics for Human Service Evaluation. Simply provide your institutional information for verification and within 72 hours you’ll be able to use your login information for any SAGE title!

Password-protected Instructor Resources include the following:

A Microsoft® Word® test bank, is available containing multiple choice, true/false, short answer, and essay questions for each chapter. The test bank provides you with a diverse range of pre-written options as well as the opportunity for editing any question and/or inserting your own personalized questions to effectively assess students’ progress and understanding.
Chapter-specific discussion questions help launch classroom interaction by prompting students to engage with the material and by reinforcing important content.

“This is definitely the right book for students and human service workers who have anxiety around statistics. It is easy to follow and one does not need any pre-knowledge of statistics to be able to use this book.”

Rashmi Gupta

San Francisco State University

“York’s text provides an easy-to-follow ‘how-to’ text for practitioners who want to evaluate client progress. It guides practitioners in the selection of appropriate statistical tests to compare groups, assess change from pre- to post-tests, and assess outcomes in single system design. York’s text is one that practitioners will want to keep on their bookcase and refer back to over the years.”

Carolyn L. Turturro

University of Arkansas at Little Rock

“This is the most comprehensive book on statistical analysis of data for human service evaluation. Social work educators, psychologists, clinicians, and sociologists would be well served in making use of this all-inclusive text.”

Jitendra Kapoor

Alabama A&M University

“This textbook empowers students to understand not only how to run statistics, but why they will run their chosen statistics. It closes the gap between ‘scary statistics’ and practical alienation of statistics in the profession.”

Marjorie C. Shavers

Heidelberg University

“The author sees data analysis and statistics through a student’s perspective. Use of a task-based approach to statistics makes it more relevant to students and easier to grasp.”

Roseanna McCleary

California State University, Bakersfield