JOURNAL OF PUBLIC AFFAIRS EDUCATION - Naspaa

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Review of The Application of Statistics to Policy Analysis and Managementdeal with samples more often than whole populations. However, the separationof inferential statistics from descriptive statistics makes it clear when inferentialstatistics are necessary and what they mean.In Chapter 9, the third workbook begins by discussing the logic of sampling.It explains the difference between the population and the sample, and explainshow random samples may or may not match the population. Rohrbaugh alsointroduces the normal curve in this chapter, along with the z-statistic. For somereason, he rounds the z-statistic to just one decimal place. Generally, scholarsround the z-statistic to at least two, if not three, decimal places. While thiscertainly helps students to remember the critical statistical levels, it may be tooimprecise for more advanced students. Additionally, he uses only the z-statistic,never the t-test for statistical significance. While this distinction may beunimportant to practitioners, the z-statistic is rarely used in inferential statistics.This is another imprecision, which shows that, while the book is useful forpractitioners and those who need to understand basic statistics, it is too imprecisefor those who wish to advance to more rigorous courses in statistical analysis.Chapters 10 and 11 cover inferences with one and two samples, respectively.Both chapters are structured in the same way, with the same relevant terms.The final chapter explains confidence intervals and the estimation of populationparameters. Rohrbaugh’s strategy for calculating statistical significance isstraightforward and can be done without a z-statistic table. He walks through thecalculation with words rather than equations, taking much of the math out of it.This last workbook truly illustrates who will benefit from the use of this text andwho might find it too remedial. Rohrbaugh’s calculation for statistical significancebegins with a decision about the level of risk of Type I Error that the studentis comfortable with. From there the student basically calculates the appropriateconfidence interval — using a z statistic rather than the standard t — and if thesample value falls outside of it, then the null is rejected. With this procedure, neitherthe t- nor the z-statistic is ever calculated. Additionally, because Rohrbaugh roundshis numbers, a z-score of 2.0 is estimated to be a 95 percent confidence interval fora two-tailed test. On the one hand, this makes it an easy calculation for practitionersand those who only require a simplistic way to judge statistical significance. Forstudents who will be continuing on to more advanced statistics, or who already havehad some statistical training, this method of calculation may seem too imprecise.There are many consistent strong points throughout all three of theworkbooks. Rohrbaugh’s exceptional use of graphics presents the materialwell. I already have mentioned his decision tree at the end of Chapter 5, butall four of his decision trees are really useful ways to help students decide notonly how to report their data, but also which types of statistics they should belooking for when they read reports. Finally, in each chapter, Rohrbaugh presentscomputations of statistics in yellow break-out boxes. These boxes walk studentsthrough the calculations of statistics in a step-by-step manner that is neither316 Journal of Public Affairs Education
Review of The Application of Statistics to Policy Analysis and Managementintimidating to look at nor to follow.John Rohrbaugh’s The Application of Statistics to Policy Analysis andManagement: An Introduction is a welcome addition to the statistics-for-socialsciencetextbook market. By creating a text with the goals of accessibilityand simplification in mind, he has not only made the study of statisticscomprehensible to students who do not think quantitatively, but he also hasre-thought the idea of what a textbook is and can be. While more quantitativeprograms likely will require a different textbook, any student who struggleswith statistics will appreciate and be able to learn from Rohrbaugh’s approach.Further, his textbook seems to be perfectly tailored to programs that teachprimarily practitioners or undergraduates. I highly recommend that professorswho teach statistics in public administration consider Rohrbaugh’s text as eitherthe main course textbook, or as a supplementary resource for students withoutprior training in statistical analysis.ReferencesGiventer, L.L. (2008). Statistical analysis for public administration (2nd ed.). Sudbury, MA: Jones and Bartlett.Healey, J. F. (2005). Statistics : A tool for social research (7th ed). Belmont, CA: Thomson/Wadsworth.Rohrbaugh, J. (2008). The application of statistics to policy analysis and management: An introduction.Albany, NY: Executive Decision Services, LLC.Sirkin, R.M. (1995). Statistics for the social sciences. Thousand Oaks, CA: Sage Publications.Andrea E. Mayo is currently a Ph.D. student in the School of Public Affairsat Arizona State University. Her primary interests include research methods,public policy analysis, the intersection of democracy and the policy process,social welfare policy, and health care policy. She has a B.A. in Sociology andAnthropology from Colgate University and a Master’s in Public Policy fromGeorgetown University.Journal of Public Affairs Education 317
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