Schedule
Public version. A generic week-by-week topic map. Specific dates, assignment prompts, and submission details live in the LMS for each section.
This site holds the public spine: short, course-voice weekly notes, public-safe Monday and Wednesday exit tickets linked from each weekly page, and outbound pointers to OpenIntro IMS and ISLBS for a second voice. Friday quizzes and the biweekly homework are handled through Blackboard or in class as directed — they are not posted here.
Week-by-week
| Wk | Topic | Notes / Activities |
|---|---|---|
| 1 | Data, evidence, and statistics | Week 1 notes — cases, variables, types; reading a small dataset honestly |
| 2 | Study design, bias, and causality | Week 2 notes — populations and samples, observational vs experimental, confounding |
| 3 | One-variable summaries | Week 3 notes — center, spread, shape; tables and graphs for a single variable |
| 4 | Comparing groups | Week 4 notes — conditional proportions, group differences, choosing the right display |
| 5 | Association | Week 5 notes — scatterplots, correlation as a descriptive number, the linear-only caveat, association vs causation |
| 6 | Confounding and multivariable thinking | Week 6 notes — confounders, stratification, Simpson’s paradox, alone vs after accounting for |
| 7 | First-half synthesis and midterm | Week 7 notes — Units 1–6 walkthrough on one connecting study; midterm-prep checklist; a single bounded forward-pointer to next week’s regression line |
| 8 | Simple regression | Week 8 notes — fitted line, slope and intercept in context, residuals and the residual-plot reading, least squares, R², extrapolation, light outliers and leverage |
| 9 | Multiple / logistic regression interpretation | Week 9 notes — adding predictors; the holding constant coefficient reading; adjusted vs unadjusted coefficients; categorical predictors; adjusted R² as a reading; interpretation-only logistic regression (direction + predicted probability) |
| 10 | Probability as risk and diagnosis | Week 10 notes — probability as risk; conditional probability and P(A | B) vs P(B | A); diagnostic two-way tables; sensitivity, specificity, predictive values; false positives/negatives; base-rate effects |
| 11 | Simulation-based inference | Week 11 notes — randomization tests, the null distribution, simulated p-values as evidence, bootstrap distributions, percentile confidence intervals, and reading StatKey-style output |
| 12 | Classical hypothesis testing | Week 12 notes — null and alternative hypotheses, the test statistic and p-value from a normal/t model, confidence intervals, reading one-proportion z and one/two-mean t output, and Type I/II errors with significance level and power |
| 13 | Categorical outcomes | planned |
| 14 | Meta-analysis and forest plots | planned |
| 15 | Final review | planned |
How to use this schedule
- Read by row. Each row gives the week’s topic and links to the notes page when it’s available. Weeks marked planned will fill in as the course is built.
- Dates live in the LMS. This site only shows “Week 1, Week 2, …” so it stays useful across terms. The LMS is the authoritative source for section-specific due dates and announcements.
- Exit tickets are linked from each weekly notes page (look for the Assignments this week section near the bottom of the page). Friday quizzes and the biweekly homework are not posted here — they are handled through Blackboard or in class as directed.
See the Syllabus for the grading framework, late-work rule, and other course-wide policies.