## PUBLIC MANAGEMENT STATISTICS

The title of this course, Public Management Statistics, is somewhat misleading. Although an integral part of the MPA program at the University of Delaware, the content and level should meet the needs of students who want or need an introduction to applied statistics. The intended audience includes social science students as well as those who are or may pursue a career in public administration pr policy analysis. Equally important, it is also serves as the first semester of two- or there-semester sequence applied statistics.

I am especially anxious that students learn a few fundamental ideas so that they can assess the strengths and limitations of quantitative policy and social science research. Who should enroll?: The class attempts to address the needs of two groups, graduate and advanced undergraduate students in the social and behavioral sciences such as sociology, economics, political science, urban affairs, history, geography, and public management.

Topics: The course provides a gentle introduction to several subjects. (If you are not familiar with these terms, suffice it to say that many of them are standard fare in most social and political science statistics courses.)

1. Personal or desktop computers and the "Windows operating" system
2. Statistical computer programs: mainly MINITAB but also SPSS.
3. Types of data and variables
4. Numerical summaries and descriptions of data
• Conventional measures of association and variation such as the mean and standard deviation.
• Exploratory data analysis (EDA) methods such as median, letter values
• Cross-classifications, rates, risk, proportions, measures of change and (in)equality.
5. Graphic descriptions of data
• Dotplots, stem-and-leaf displays, histograms, quantile plots, boxplots
• Scatterplots
• Time series and semi-logarithmic plots
6. Simple models for describing the interrelationships among variables.
• Correlation and other measures of association
• Regression
• Analysis of covariance
7. Basics of statistical inference
• Probability
• Principles of hypothesis testing and estimation
• Test of means, differences of means, and proportions.
• Confidence intervals
• Statistical power analysis
8. Issues in research methods
• Causation versus correlation
• Measurement

Prerequisites: Practically none except a good attitude. Understanding the material requires no mathematical background other than high school algebra. Nor do you need to know much about computers since I provide instruction every step of the way. You will, however, have lots of work especially since I believe statistics is best learned by doing.