Notes

The weekly assumption-light methods spine

The notes are the backbone of the course. There is one note per week, and reading the current week’s note before class — and again after — is the single most reliable way to keep up. Every note follows the same shape, so once you learn to read one, you can read them all.

How to read a week

Each weekly note is built from the same parts, in the same order. Knowing the anatomy lets you skim for what you need and study with intent:

The week question. A single question that the week exists to answer. Hold it in mind as you read; everything else is in service of it.
Concept development. The core ideas, built up in a few short sections from intuition toward a precise statement about what the method assumes and what it claims. This is the part to read slowly — and where the assumption ladder (what is assumed, what is resampled/ranked/downweighted, what is protected against, what cannot be proven) is made explicit.
Worked examples. Each idea is worked on the recurring Riverside Wellness world — the wait-time comparison, the paired before/after wellbeing scores, the satisfaction ratings, or the contaminated engagement-vs-gain scatter — with the setup, the computation shown in R, and the result interpreted in sentences — plus one transfer example in a fresh context, so you see the idea move.
A common mistake. The resampling/rank/robust error students most often make on this topic — permuting the wrong thing, treating a bootstrap interval as assumption-free, reading a rank test as a mean difference, deleting an outlier silently — named plainly so you can watch for it in your own work.
Ungraded self-checks. A few low-stakes practice prompts to test yourself. These are self-check only — no points, no submission.
Reading pointer. Where to read more: the relevant Introduction to Modern Statistics topic (and, for the workflow weeks, ModernDive; for the classical rank-based weeks, the optional Nonparametric Statistical Methods), with the reminder that these notes are the course’s own synthesis.
Evidence and verification status. An honest note that the numbers in the example datasets are drafted and synthetic, pending review — this is a draft course site.
Looking ahead. A sentence or two connecting this week to the next, so the arc stays visible.

Keep the methods glossary and the method chooser open alongside the notes.

The four parts

The fifteen weeks fall into four parts. Each part has a job, and the weeks within it build on one another.

Part I — Foundations of assumption-light reasoning. Why weaker assumptions are useful, and the empirical objects the course is built on.

Part II — Resampling inference. Inference built from the data itself: shuffle to test, resample to estimate.

Part III — Rank-based & ordinal methods. Methods that use order, not the raw numbers.

Part IV — Robustness, comparison & synthesis. Resistant summaries, robust regression, method comparison, a simulation study, and a closing synthesis.

Public vs. graded

These notes and the practice in them are public and ungraded — study material only. No graded prompts, answer keys, rubrics, point values, or due dates appear on this site. Graded method checkpoints, quizzes, homework and method reports, resampling and robustness labs, the midterm, the applied robust-methods project, and the final exam live in Blackboard (the LMS), which is authoritative for due dates, submissions, and grades. If this page and Blackboard ever disagree, follow Blackboard.