Title: Week 12 — Readings & Resources · Confidence Intervals for a Proportion
Course: Introduction to Statistics (18-Week Generic Edition)

Course: Introduction to Statistics (18-week generic edition) Objective covered: Objective 6 — Construct and interpret confidence intervals for a population proportion, and determine the sample size a target margin of error requires. Your primary reading is Chapter 12 (in this module). 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 week's three big ideas. 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 what a confidence interval is & what "95% confident" really promises → ② building the one-proportion z-interval (conditions, standard error, z*) → ③ choosing a sample size & reading the margin of error in real polls.

A habit to start now: every time one of these resources shows you a percent, ask the week's three questions — Who was sampled, and how? What's the whole interval? What could bias this that the ± doesn't cover?

① The Interval Idea · What "95% Confident" Promises

Maps to Chapter 12, Sections 1 and 3 and Lecture Segments 2–4. The line to carry: the confidence lives in the method — about 19 of every 20 random samples produce an interval that captures the truth.

Reading — Understanding Confidence Intervals: Easy Examples & Formulas (Scribbr) 🔗 https://www.scribbr.com/statistics/confidence-interval/ Why it's assigned: the cleanest plain-language tour of the interval idea, with the z multipliers laid out and a dedicated section on the proportion formula — the same p̂ ± z·SE anatomy as our chapter. ⏱ ~8 min

Video — Confidence Intervals: Crash Course Statistics #20 (video, ~13 min, captioned) 🔗 https://www.youtube.com/watch?v=yDEvXB6ApWc Why it earns the click: the liveliest walk through what an interval does and doesn't claim — including the "it's about the method, not your one interval" point our quiz loves.

Video — Confidence Intervals, Clearly Explained!!! (StatQuest with Josh Starmer) (video, ~6 min, captioned) 🔗 https://www.youtube.com/watch?v=TqOeMYtOc1w Why it earns the click: six minutes that make the "19 out of 20" picture stick — you watch many intervals get built and see which ones capture the truth.

② Building the One-Proportion z-Interval

Maps to Chapter 12, Section 2 and Lecture Segments 2–3. Remember the password before any build: random · at least 10 successes and 10 failures · population ≥ 10n — and the formula eats proportions, never counts.

Reading — 8.1 One Sample Proportion (Penn State STAT 200 online notes) 🔗 https://online.stat.psu.edu/stat200/lesson/8/8.1 Why it's assigned: a compact university treatment of the sampling distribution of p̂ and the normal-approximation interval — a second voice on exactly our conditions and standard error. ⏱ ~8 min

Reading — 8.3 A Population Proportion (OpenStax Introductory Statistics 2e) 🔗 https://openstax.org/books/introductory-statistics-2e/pages/8-3-a-population-proportion Why it's assigned: the full textbook version with several worked examples — including sample-size determination — if you want one source that goes end to end. (It also shows a "plus four" adjustment we do not use; our course sticks to the standard z-interval.) ⏱ ~12 min

③ Sample Size · Polls & the Margin of Error in the Media

Maps to Chapter 12, Sections 4–5 and Lecture Segments 5–6. Two laws to keep: the bill always rounds up, and the margin shrinks like 1 ⁄ √n — half the margin costs four times the crowd.

Reading — 5 key things to know about the margin of error in election polls (Pew Research Center) 🔗 https://www.pewresearch.org/short-reads/2016/09/08/understanding-the-margin-of-error-in-election-polls/ Why it's assigned: a professional polling house explains, in plain English, what its own ±3 covers and what it doesn't — subgroups, lead sizes, and the non-sampling errors that ride outside the margin. The perfect companion to this week's Data Lab. ⏱ ~7 min

Video — Confidence Intervals for a Proportion: Determining the Minimum Sample Size (jbstatistics) (video, ~7 min, captioned) 🔗 https://www.youtube.com/watch?v=mmgZI2G6ibI Why it earns the click: a calm, careful walkthrough of the exact sample-size formula from lecture — including the conservative p* = 0.5 move and why the answer always rounds up.

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 8 (Confidence Intervals) covers this week and last week end to end — means, proportions, and sample size. 🔗 https://openstax.org/books/introductory-statistics-2e/pages/8-introduction Why it's here: a reputable, currently-available reference for the whole confidence-interval story — entirely optional this week.

Pick-one quick path (≈20 min total)

In a hurry? You've read Chapter 12 — then do exactly these three and you'll be ready for the quiz: 1. Watch StatQuest — Confidence Intervals, Clearly Explained!!! (group ①). 2. Read Penn State STAT 200 — 8.1 One Sample Proportion (group ②). 3. Read Pew Research — 5 key things about the margin of error (group ③).

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.