The syllabus gives the course description, contact information, grading scheme, and other course information.


Class notes

  1. Getting started. (R code). (Annotations).

  2. Matrices for applied statistics. (R code). (Annotations).

  3. Fitting a linear model to data by least squares. (R code). (Annotations).

  4. Probability models. (R code). (Annotations).

  5. Vector random variables. (R code). (Annotations).

  6. Confidence intervals and hypothesis testing. (R code). (Annotations).

  7. Factors and the ANOVA F-test. (R code). (Annotations).

    Discussion: STATS 401 and the future of undergraduate data science. (Feedback).

  8. Model diagnostics. (R code). (Annotations).

  9. Additional topics in linear modeling. (R code). (Annotations).


Homework assignments


Lab materials


Quiz materials


Midterm exam materials


Final exam materials