This page contains link to the lectures I give throughout the semester. Clicking the title of the week’s lecture will go to a PDF, embedded in the user’s browser, by default. The bottom left icons link to the Github directory for the lecture (), the R Markdown document for the lecture (), and a PDF, embedded on Github, for the lecture ().

  • Univariate Analysis
    tl;dr: An introduction to the course, a rudimentary statement of basic research design, an emphasis our concept-laden qualitative world, and the ways we can measure it and describe what we see. Is that all? Yeah, actually. Yeah. That's all for this lecture.
         
  • Bivariate Analysis
    tl;dr: There are multiple ways you can make bivariate comparisons/associations. This lecture mentions a lot of them, but privileges chi-square tests, Pearson's r, and the t-test.
         
  • The Linear Model and OLS
    tl;dr: A quick crash course on what the linear model is, what OLS does, how you can use it, and communicate/inspect its output.