Title: Week 14 — Readings & Resources · Testing Claims About Means
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 (the means portion: one-sample and paired t procedures). Your primary reading is Chapter 14 (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 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-sample t-test recipe → ② from t to verdict (tails, cutoffs, p-values) → ③ paired before/after data → ④ full worked examples, start to finish.

A habit for this week: every time a source shows a test, find the moment the analyst divides by s∕√n — not s — and the moment the cutoff comes from the t-table row df = n − 1. Those two moments are where this week's classic mistakes live.

① The One-Sample t-Test — the Recipe

Maps to Chapter 14, Section 1 and Lecture Segment 2. The whole test in one line: a t-statistic counts standard errors between the data and the claim.

Reading — An Introduction to t Tests: Definitions, Formula and Examples (Scribbr) 🔗 https://www.scribbr.com/statistics/t-test/ Why it's assigned: the cleanest plain-language tour of what a t test is and the one-sample/two-sample/paired family — a preview of next week's branches with this week's recipe at the center. ⏱ ~7 min

Video — t Tests for One Mean: Introduction (jbstatistics) (video, ~6 min, captioned) 🔗 https://www.youtube.com/watch?v=T9nI6vhTU1Y Why it earns the click: the hypotheses, the t-statistic, and the df idea built up carefully in six minutes — the exact skeleton of our courier example.

② From t to Verdict — Cutoffs, Tails & p-Values

Maps to Chapter 14, Sections 1–2 and Lecture Segments 2–3. Remember the reading rule: two-sided at α = 0.05 → the table's 95% column; one-sided at 5% → the 90% column. And pick your tail before you peek.

Reading — The One-Sample t-Test (JMP Statistics Knowledge Portal) 🔗 https://www.jmp.com/en_us/statistics-knowledge-portal/t-test/one-sample-t-test.html Why it's assigned: a complete worked test — hypotheses, statistic, critical-value comparison, p-value — with the clearest pictures anywhere of what the cutoff actually cuts. ⏱ ~9 min

Video — t Tests for One Mean: An Example (jbstatistics) (video, ~9 min, captioned) 🔗 https://www.youtube.com/watch?v=kQ4xcx6N0o4 Why it earns the click: one real test run end to end — including the p-value read and the verdict-in-context sentence this course grades.

③ Paired Before/After Data

Maps to Chapter 14, Section 3 and Lecture Segment 5. The hook: pairs? subtract first — then it's one sample.

Reading — The Paired t-Test (JMP Statistics Knowledge Portal) 🔗 https://www.jmp.com/en_us/statistics-knowledge-portal/t-test/paired-t-test.html Why it's assigned: shows exactly how two linked columns collapse into one column of differences, with a worked before/after example that parallels our typing-course test. ⏱ ~9 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 explanation of why pairing helps — each subject as their own control — plus the t-distribution's role, all in one sitting.

④ Full Worked Examples, Start to Finish

Maps to Chapter 14, Sections 1–3 and the whole lecture. Use this when you want every step of a formal write-up — hypotheses through conclusion — spelled out.

Reading — 10.4 Matched or Paired Samples (OpenStax Introductory Statistics 2e) 🔗 https://openstax.org/books/introductory-statistics-2e/pages/10-4-matched-or-paired-samples Why it's assigned: three fully worked paired tests written in careful formal style — the level of completeness your assignment write-ups should imitate. ⏱ ~10 min

Optional one-stop reference (free online text)

If you'd like one optional reference to skim all term, OpenStax Introductory Statistics 2e keeps its full text free to read online. Chapter 9 (Hypothesis Testing with One Sample) covers this week's testing machinery end to end — and pairs naturally with Section 10.4 above for the paired case. 🔗 https://openstax.org/books/introductory-statistics-2e/pages/9-introduction Why it's here: a reputable, currently-available reference you can return to in later weeks — entirely optional this week.

Pick-one quick path (≈25 min total)

In a hurry? You've read Chapter 14 — then do exactly these three and you'll be ready for the quiz: 1. Watch t Tests for One Mean: Introduction (group ①). 2. Watch t Tests for One Mean: An Example (group ②). 3. Watch Crash Course #27 — T-Tests: A Matched Pair Made in Heaven (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.