THIS COURSE WILL BE AVAILABLE STARTING JANUARY 2019.
This course helps you start that research project, for that course paper, that masters thesis, that dissertation proposal. Maybe even that doctoral dissertation.
It brings together the knowledge and skills taught in program evaluation (sometimes called research design), statistics, econometrics (sometimes called linear regression), and dataset management. The course presumes some familiarity with these knowledge and skill areas, but not expertise. Which means the course is for you even if you haven't finished all of your core course work in public policy, public management, or public health.
Here's the part where you get excited about the course:
Each lecture is focused on a singular quasi-experimental (QE) research design - e.g., pretest-posttest with a nonequivalent comparison group, single group interrupted time series, etc. Each lecture describes and explains how to structure, clean, and code your dataset per the focal QE research design, or, in contrast, how to reverse engineer a QE research design from your dataset, given your research question(s). Each lecture then describes and explains what statistical tests to perform for the focal QE research design, why to perform said statistical tests, why not to perform other tests, and, best of all, how to specify the model in your statistical software package so your tests run smoothly. What's more, you will have *direct access* to the professor in the case that none of the lectures help you to figure out specifically what you need to do to get your dataset ready, understand fully its strengths and weaknesses with regard to drawing causal inferences, and so on.
The course content will remain available to you for the temporal run of a typical academic semester, i.e., 15 weeks.
It is highly recommended that you take the FREE course offerings from
Applied Public Policy & Management Knowledge Base before taking
Or if you have your ducks in a row and are ready to start writing up your results and the rest of your paper - the intro, lit review, hypotheses, discussion, conclusion, and so on, the below course may be a better fit for your current needs:
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In the 10+ years since earning my doctorate in public policy from Georgia Tech, I've shepherded more than a thousand undergrad and grad students through their public policy and management coursework and exit requirements. I'm quite good at, and really enjoy, helping students to make those critical yet implicit connections between evaluation/research design, dataset development, analytic methods, and model specification. I'm also quite good at, and also really enjoy, helping students to see the forest for the trees and, in doing so, to dominate their coursework, comprehensive exams, exit requirements, and budding careers. I am a prolific academic writer, with more than 30 peer-reviewed journal articles in top journals as well as 2 books and tens of book chapters, and numerous technical reports for government agencies, who has successfully and quickly and many times over turned bad paper (and thesis and article) writers into very good paper (and thesis and article) writers.
Currently, in addition to tutoring clients via this medium, I am funded by a research grant from the US National Science Foundation. In 2013 I received tenure from one of the largest research universities in the US and before that I was a consultant in Washington, DC. My past clients include individuals and groups working at the White House, the US National Science Foundation, the US National Institutes of Health, the National Research Council, and, internationally, the OECD.
For course correspondence requiring attachments, e.g., paper drafts, please use [email protected]