Week 11 — Readings & Resources

Your primary reading is Chapter 11 (in this module). Everything below is the optional, go-deeper layer — pick what helps, skip the rest.

How to use this page

This page has 10 items (4 readings and 6 videos). Allow 75–89 minutes for everything. Each group points back to the matching chapter section and class-session segment, so use the full menu when you want more practice, or take the quick path below.

Every video here has captions: turn them on with the CC button in the player. The chapter covers the same ideas in text.

Pick-one quick path (18–22 min total)

• Confidence Intervals — Math is Fun
• Confidence Intervals for One Mean: Sigma Not Known (t Method) — jbstatistics

① Why a range beats one number

Chapter 11, Section “Interval estimates: turn the wobble into a range” · Session 1, Segment 1, “From a point estimate to an interval” · Remember: an interval estimate is a point estimate plus or minus a margin of error, so the reader sees both the guess and its wobble.

• Confidence Intervals: Crash Course Statistics #20 — CrashCourse — a fast tour of why a range is more honest than one number. It uses delivery windows and polls. Notice any line that puts a chance on one finished interval. Then compare it with the chapter's wording. Stop here before intervals for a proportion; next week takes that up. (video, 13 min) (captions: creator)
• Understanding Confidence Intervals: Statistics Help — Dr Nic's Maths and Stats — a short, calm talk with diagrams. It shows what an interval estimate is. It also shows why the range sits around the sample's own mean. (video, 4 min) (captions: creator)
• Confidence Intervals — Math is Fun — the gentlest page on this list. Read the height example and the part on what 95% means. It gives the same 19-in-20 idea as the die example in the chapter. It uses 1.96, not t*, which is close for large samples. This builds on Week 10's work with the sampling distribution of the sample mean and the standard error. (reading, 8–12 min)

② Building the t interval, by hand and by spreadsheet

Chapter 11, Section “The one-sample t interval: build it by hand and by spreadsheet” · Session 1, Segment 2, “The t distribution and the one-sample t interval” · Remember: when the population standard deviation is unknown, use the sample standard deviation and a t distribution with the sample size minus 1 degrees of freedom.

• Introduction to the t Distribution (non-technical) — jbstatistics — a careful look at how a t curve compares with the normal curve. Its heavier tails give small samples a larger critical value. (video, 9 min) (captions: creator)
• Confidence Intervals for One Mean: Sigma Not Known (t Method) — jbstatistics — one full interval from a small sample of cereal boxes. It goes step by step, from the degrees of freedom to the two ends. (video, 10 min) (captions: creator)
• Calculate a 95% Confidence Interval: 2 Methods, CONFIDENCE.T Function and the Analysis ToolPak — Chester Tugwell — the spreadsheet route. CONFIDENCE.T gives the margin of error in one step, and it works in Google Sheets too. Use it while completing the Week-11 module overview. (video, 5 min) (captions: automatic)
• Understanding the t-distribution and its normal approximation — R Psychologist — an interactive page. Read the short opening on why estimating the variance from a sample gives the t distribution heavier tails. Then slide the degrees of freedom up and watch the t curve close in on the normal curve. Skip the quantile plot and the two error plots. (reading, 4–7 min)

③ What "95% confident" does and does not mean

Chapter 11, Section “The confidence level: what 95% does and does not mean” · Session 2, Segment 3, “Interpreting the interval and the confidence level” · Remember: the 95% describes the method's long-run capture rate, not one finished interval and not the share of individuals inside it.

• Confidence Interval: The right and wrong way to understand them — numiqo — a direct look at the most common ways people misread an interval. It ends with the right reading. The chapter's last section names the same trap. (video, 11 min) (captions: automatic)
• Frequentist Inference — Seeing Theory — an interactive visualization page. In the Confidence Interval part, press start and watch many intervals pile up. Count how many miss the true mean. Then change the level and the sample size. (reading, 6–10 min)

Optional one-stop reference (free online reference)

• 1.3.5.2. Confidence Limits for the Mean — NIST/SEMATECH e-Handbook of Statistical Methods — a free government reference. Read the purpose, the definition, and the interval example. Skip the test parts and the software notes. (reading, 5–8 min)

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 reference above in the meantime.

Provenance: Built with The Course Maker · samples.thecoursemaker.com