Title: Week 15 — Readings & Resources · Testing Proportions & Two-Sample Inference
Course: Introduction to Statistics (18-Week Generic Edition)

Course: Introduction to Statistics (18-week generic edition) Objective covered: Objective 7 — conduct and interpret hypothesis tests for proportions and two-sample comparisons of means and proportions. Your primary reading is Chapter 15 (in this module — it re-prints the friendly z-table). Everything below is the optional, go-deeper layer.

How to use this page

Everything here is a link to an external resource — open it in your browser, the same way you'd open a YouTube link. Nothing needs to be downloaded, and nothing costs money.

The load is deliberately light: 4 short readings + 3 short videos, grouped by the four big ideas of the week. Read or watch one item per group and you're well prepared; do all of them and you'll be very comfortable. Total time is roughly 55–65 minutes if you do everything, far less if you pick one per group.

Order that matches the chapter and lecture: ① the one-proportion z-test → ② comparing two proportions (and why the test pools) → ③ two-sample t for means (and the paired reminder) → ④ choosing the right procedure.

A habit for this week: every time a resource reports a test result, ask the two questions before accepting the conclusion — was anything randomly assigned? (that decides causal language) and how big is the difference in real units? (significance alone never answers that).

① The One-Proportion z-Test

Maps to Chapter 15, Sections 1–2 and Lecture Segments 2–3. The recipe: hypotheses about p, SE from p₀ (the null's own yardstick), z, p-value, decision. Interval → p̂; test → p₀.

Reading — Hypothesis Test for a Proportion (Stat Trek) 🔗 https://stattrek.com/hypothesis-test/proportion Why it's assigned: a clean five-step walkthrough of exactly our test — including the large-count conditions and both one- and two-tailed worked examples that mirror the chapter's seed-packet logic. ⏱ ~8 min

Video — Calculating a z statistic in a test about a proportion | AP Statistics (Khan Academy) (video, ~5 min, captioned) 🔗 https://www.youtube.com/watch?v=DfpFfIdwcIo Why it earns the click: watches the statistic get assembled piece by piece — p̂, p₀, the SE built from p₀ — which is precisely the step students most often reverse.

② Comparing Two Proportions

Maps to Chapter 15, Section 3 and Lecture Segment 4. The one new idea: under H₀ the groups share ONE rate, so the SE is built from the pooled proportion — the null doing its own arithmetic.

Reading — Hypothesis Test: Difference Between Proportions (Stat Trek) 🔗 https://stattrek.com/hypothesis-test/difference-in-proportions Why it's assigned: states the two-proportion test the way our printouts do — and it is explicit about when and why the pooled proportion enters the standard error, the exact point the quiz probes. ⏱ ~9 min

Video — An Introduction to Inference for Two Proportions (jbstatistics) (video, ~11 min, captioned) 🔗 https://www.youtube.com/watch?v=g0at6LpYvHc Why it earns the click: a calm, precise development of the sampling distribution of p̂₁ − p̂₂ — the "why" behind every number on the two-proportion printout you'll read this week.

③ Two-Sample t for Means (and the Paired Reminder)

Maps to Chapter 15, Sections 4–5 and Lecture Segments 5–6. Same story as proportions, with t in place of z, no pooling, and df read off the printout — plus Week 14's tell: same individuals twice → paired.

Reading — An Introduction to t Tests | Definitions, Formula and Examples (Scribbr) 🔗 https://www.scribbr.com/statistics/t-test/ Why it's assigned: puts one-sample, two-sample, and paired t-tests side by side with plain-language rules for telling them apart — the exact judgment call in this week's "which procedure?" items. ⏱ ~7 min

Video — T-Tests: A Matched Pair Made in Heaven: Crash Course Statistics #27 (CrashCourse) (video, ~11 min, captioned) 🔗 https://www.youtube.com/watch?v=AGh66ZPpOSQ Why it earns the click: the liveliest tour of two-sample and paired t-tests in one sitting — and it lands hard on why pairing changes the analysis, this week's classic trap.

④ Choosing the Right Procedure

Maps to Chapter 15, Section 5 and Lecture Segment 6. Two questions pick the tool: counting successes or measuring amounts? one sample, two samples, or the same individuals twice?

Reading — Choosing the Right Statistical Test | Types & Examples (Scribbr) 🔗 https://www.scribbr.com/statistics/statistical-tests/ Why it's assigned: a flowchart-style guide from data type to test — a grown-up version of this week's procedure map that also previews tests you'll meet later (chi-square is next week). ⏱ ~8 min

Optional one-stop reference (free online text)

If you'd like one optional reference to skim, OpenStax Introductory Statistics 2e keeps its full text free to read online. Chapter 10 (Hypothesis Testing with Two Samples) covers this week's comparisons end to end — two means, two proportions, and matched pairs. 🔗 https://openstax.org/books/introductory-statistics-2e/pages/10-introduction Why it's here: a reputable, currently-available reference you can return to during final-exam review — entirely optional this week.

Pick-one quick path (≈20 min total)

In a hurry? You've read Chapter 15 — then do exactly these three and you'll be ready for the quiz: 1. Read Hypothesis Test for a Proportion (group ①). 2. Watch jbstatistics — An Introduction to Inference for Two Proportions (group ②). 3. Read Choosing the Right Statistical Test (group ④).

Heads-up (links rot): these point to outside sites that occasionally move or rename pages. If a link ever fails, tell your instructor and use the OpenStax reference above in the meantime.