Compassionate Statistics: Applied Quantitative Analysis for Social Services (with Exercises and Instructions in SPSS)
By: Vincent E. Faherty (author)Paperback
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Designed as a companion manual to mainstream methods textbooks, this text provides a comprehensive, yet pragmatic, resource for social service professionals to use standard descriptive and inferential statistical techniques in ways that are meaningful to them, to their social agencies, to their funding sources, and, ultimately, to their clients.
Vincent Faherty earned his doctorate in Social Work (DSW) from the University of Utah in 1976. He also holds a Master of Business Administration degree (MBA) from the International Management Institute of the University of Geneva (1985), a Master of Social Work degree from Fordham University (1970), and a Bachelor of Arts degree from Cathedral College & Seminary (1958). He has taught statistics and social work research methods for the past 18 years at the University of Southern Maine. Prior to that, he taught at the University of Northern Iowa and at the University of Columbia-Missouri.
Acknowledgments 1. Introduction, Overview, and Nondefinitions 2. Levels of Data: Nominal, Ordinal, and Scale 3. Presenting Data in Tables 4. Presenting Data in Figures 5. The 3 Ms: Mean, Median, and Mode 6. Standard Deviations, Ranges, and Quartiles 7. Other Descriptive Statistics 8. Probability and Statistical Significance 9. Chi-Square Test of Independence 10. Correlation: Scattergrams 11. Correlation: Spearman's rho and Pearson's r 12. t-Test for Paired Samples 13. t-Test for Independent Samples 14. One-Way Analysis of Variance (ANOVA) With Post Hoc Tests 15. Nonparametric Alternatives to Common Parametric Tests Appendix A: Getting Started With SPSS Appendix B: SPSS Data Sets Appendix C: Outline of Common Univariate and Bivariate Statistical Procedures Appendix D: Outline of Common Parametric and Nonparametric Inferential Tests Appendix E: Table of Random Numbers With Instructions Appendix F: Glossary of Terms Index About the Author
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