Both practical and easy to read, Rubin's STATISTICS FOR EVIDENCE-BASED PRACTICE AND EVALUATION provides you with a step-by-step guide that will help you succeed in your course. Practice illustrations and exercises support your ability to study and retain core concepts, while practical examples provide you with the opportunity to see how and when data analysis and statistics are used by helping professionals in the real world.
Both practical and easy to read, Rubin's STATISTICS FOR EVIDENCE-BASED PRACTICE AND EVALUATION provides you with a step-by-step guide that will help you succeed in your course. Practice illustrations and exercises support your ability to study and retain core concepts, while practical examples provide you with the opportunity to see how and when data analysis and statistics are used by helping professionals in the real world.
Part 1: INTRODUCTION AND EVIDENCE-BASED PRACTICE.
1. Why Study Statistics?
2. Use of Statistics in Evidence-Based Practice.
3. Review of Key Research Methodology Concepts and Terms.
Part 2: DESCRIPTIVE STATISTICS.
4. Frequency Distributions.
5. Graphs and Charts.
6. Measures of Central Tendency.
7. Measures of Dispersion.
8. Types of Distributions.
9. z-Scores, Percentiles, and Effect Size.
Part 3: INFERENTIAL DATA ANALYSIS: CONCEPTUAL FOUNDATION.
10. Probability and Sampling Distributions.
11. Hypothesis Testing and Statistical Significance.
12. Type I and Type II Errors.
13. Interpreting the Strength and Importance of Relationships.
Part 4: INFERENTIAL DATA ANALYSIS: PARAMETRIC AND NONPARAMETRIC
PROCEDURES.
14. The t-Test.
15. Analysis of Variance.
16. Cross-Tabulation and Chi-Square.
17. Correlation.
18. Regression Analysis.
19. Applications to Single-System Evaluation Designs.
Appendix A: Review of Some Math Basics.
Appendix B: Statistical Symbols.
Appendix C: A Conceptual Overview of Factor Analysis.
Appendix D: A Conceptual Overview of Discriminant Analysis.
Appendix E: A Conceptual Overview of Logistic Regression.
Appendix F: A Conceptual Overview of Multilevel Modeling
(Hierarchical Linear Models).
Appendix G: A Conceptual Overview of Path Analysis.
Appendix H: A Conceptual Overview of Structural Equation
Modeling.
Appendix I: A Conceptual Overview of Event History Analysis
(Survival Analysis).
Appendix J: Reporting Your Statistical Findings.
Appendix K: Preparing Data for Analysis.
Appendix L: Hypothetical Data Set for SPSS.
Appendix M: SPSS Instructions and Exercises.
Glossary.
References.
Index.
Allen Rubin has been doing and teaching research since 1976, when he received his Ph.D. from the University of Pittsburgh. He taught social work research at the University of Texas at Austin from 1979 through 2013 and at the University of Houston from 2013 through 2024. Renowned in social work, Dr. Rubin has written several research texts, published numerous research studies on social work practice and is a past president of the Society for Social Work and Research.
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