Rachel G. Kleit
PB AF 528
Second quarter of a two-quarter sequence aimed at helping students become informed users and critical consumers of research and statistical analysis. Combines material on research design and data collection methods with tools for multivariate analysis. The multivariate analysis methods include correlation and an introduction to multivariate regression. Prerequisite: PB AF 527.
This course is the second in a two-course sequence aimed at helping Evans School MPA students become informed users and critical consumers of research and statistical analyses. This course introduces the application of probability, hypothesis testing, and confidence intervals to multivariate models in the context of policy and management research.
Student learning goals
By the end of this course, you will: · Formulate answerable research questions that address complex policy questions. · Be aware of the conditions necessary to establish causal relationships on a given outcome, emphasizing the need to disentangle the effects of multiple factors. · Recognize the implications of research design choices, randomization, concept measurement, and good data collection for the validity and reliability of research results. · Discriminate among data collection methods appropriate to answer a given research question, such as surveys, focus groups, key informant interviews, administrative data, or other methods. · Select appropriate univariate, bivariate, or multivariate analytic techniques to answer a given policy or management question. · Understand the mechanics, assumptions, and interpretation of regression models to policy or management questions, how to use regression models for both prediction and hypothesis testing, and the assumptions behind and possible "fixes" for problems with models. · Read and analyze empirical studies · Produce a useful multivariate empirical analysis for a non-statistician, including clear data presentation and the graphical display of data. · Recognize how policy analysis, program evaluation, and performance measurement employ research methods and statistical techniques. · Be exposed to nonlinear models and understand their purposes.
General method of instruction
Instruction includes lecture, in-class exercises, discussion, and homework assignments.
Class assignments and grading
Assignments allow students to use their own data using SPSS or Excel to learn regression and build up to their final paper.
Homework assignments 1-4 (complete and on time) 10% Homework assignment 5 10% In-Class Quiz I (April 22-open book and notes) 15% In-Class Quiz II (May 9-open book and notes) 15% Policy Report 50%