Title: Week 15 — you're in an experiment right now
Course: Introduction to Statistics (18-Week Generic Edition)

Hi everyone,

Quick claim before we start: sometime this week, an app will experiment on you. One version of a screen for you, another for someone else, a counter ticking in the background. Nobody will ask. The tech world calls it an A/B test — and by the end of this week, you'll know the exact statistics behind it, because it's this course's machinery pointed at two groups at once.

This week — Testing Proportions & Two-Sample Inference — closes the everyday testing toolbox: the one-proportion z-test (is a claimed percentage true?), the two-proportion z-test and the two-sample t-test (do two groups really differ?), and the map for picking the right tool on sight. Last week you put means on trial; this week percentages and pairs of groups take the stand.

Three things not to miss: 1. Chapter 15 is your primary reading — it re-prints the friendly z-table and carries every worked example the week leans on. Start there. 2. Data Lab 15 — "Split the Traffic" — you'll rig two checkout pages where YOU know the truth, simulate 400 shoppers, and watch the test catch the difference… most of the time. The runs that miss are the whole lesson. Due at the end of Week 15. 3. Discussion 15 — "The Everyday A/B Test" wants your initial post two days before the week ends — come argue about whether silent experiments on users need consent, and when a "significant" win should actually ship.

One heads-up for the AI work: this week your chatbot will confidently tell you that a non-significant result means "the groups are the same." In the lab, you'll know the truth and it won't — catching that mistake is graded. The tool drafts; you judge.

Next stop after this: categorical data get a test of their own (chi-square), and then the story wraps. The toolbox is nearly full — come get its two most-used tools.

See you in the course!