Title: Week 3 — Readings & Resources · Numerical Summaries: Center & Spread
Course: Introduction to Statistics (18-Week Generic Edition)

Course: Introduction to Statistics (18-week generic edition) Objective covered: Objective 2 — Summarize and display univariate data. Your primary reading is Chapter 3 (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 + 4 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 60–70 minutes if you do everything, far less if you pick one per group.

Order that matches the chapter and lecture: ① mean / median / mode → ② spread & the standard deviation → ③ five-number summary, boxplots & the outlier rule → ④ z-scores as relative standing.

A habit to keep from Week 1: every summary number you meet in these resources came from a sample somebody collected — the week's new question to ask on top of who was measured is which summary did they choose, and what would the other one have said?

① Three Centers: Mean, Median & Mode

Maps to Chapter 3, Sections 1–2 and Lecture Segments 2–3. The hook to keep: mean = balance point, median = middle person, mode = most common — and only the median shrugs at outliers.

Reading — Central Tendency: Understanding the Mean, Median & Mode (Scribbr) 🔗 https://www.scribbr.com/statistics/central-tendency/ Why it's assigned: the cleanest side-by-side of all three centers, including how skew decides which one to trust — the exact judgment call this week's quiz and assignment ask you to make. ⏱ ~7 min

Video — Mean, Median, and Mode: Measures of Central Tendency: Crash Course Statistics #3 (video, ~11 min, captioned) 🔗 https://www.youtube.com/watch?v=kn83BA7cRNM Why it earns the click: a lively tour of the three centers with real-world skewed examples — you'll watch a single extreme value drag a mean, exactly like the crash-day commute.

② Spread & the Standard Deviation

Maps to Chapter 3, Section 3 and Lecture Segment 5. The sentence that matters: the SD is the typical distance from the mean — and samples divide by n − 1.

Reading — How to Calculate Standard Deviation: Guide, Calculator & Examples (Scribbr) 🔗 https://www.scribbr.com/statistics/standard-deviation/ Why it's assigned: walks the same six-step recipe as our worked example — deviations, squares, n − 1, root — and explains the sample-vs-population divisor that trips up both students and chatbots. ⏱ ~8 min

Video — Measures of Spread: Crash Course Statistics #4 (video, ~12 min, captioned) 🔗 https://www.youtube.com/watch?v=R4yfNi_8Kqw Why it earns the click: range, IQR, variance, and SD in one sitting, with the "why we square the deviations" moment shown visually.

Video — Calculating the Mean, Variance and Standard Deviation, Clearly Explained!!! (StatQuest with Josh Starmer) (video, ~15 min, captioned) 🔗 https://www.youtube.com/watch?v=SzZ6GpcfoQY Why it earns the click: the slowest, gentlest walk through why the sample formula divides by n − 1 — watch this if the divisor still feels arbitrary after the lecture.

③ Five-Number Summary, Boxplots & the Outlier Rule

Maps to Chapter 3, Section 4 and Lecture Segment 6. Remember the pairing rule: mean travels with SD; median travels with IQR — and outliers get flagged by fences, not feelings.

Reading — How to Find the Interquartile Range (IQR): Calculator & Examples (Scribbr) 🔗 https://www.scribbr.com/statistics/interquartile-range/ Why it's assigned: quartiles, the IQR, and the boxplot connection with worked numbers — it also shows two quartile conventions, which explains why your spreadsheet's =QUARTILE can disagree with your pencil. ⏱ ~7 min

Video — Boxplots are Awesome!!! (StatQuest with Josh Starmer) (video, ~5 min, captioned) 🔗 https://www.youtube.com/watch?v=fHLhBnmwUM0 Why it earns the click: five minutes that make boxplots feel obvious — the box, the median line (not the mean!), the whiskers, and the flagged dots, exactly as the data lab asks you to read them.

④ z-Scores: Relative Standing

Maps to Chapter 3, Section 5 and Lecture Segment 7. The formula is one line — z = (value − mean) ÷ SD — and the payoff is comparing things that live on different scales.

Reading — Z-score: Definition, Formula, and Uses (Statistics By Jim) 🔗 https://statisticsbyjim.com/basics/z-score/ Why it's assigned: clear worked z-score comparisons across different scales (his apples-vs-oranges example mirrors our two-exam problem), plus a preview of how z-scores will connect to the normal model later in the course — skim that part, it's not needed yet. ⏱ ~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 2 (Descriptive Statistics) covers this week end to end — measures of center, measures of spread, box plots, and outliers (its early sections revisit last week's graphs, a free review). 🔗 https://openstax.org/books/introductory-statistics-2e/pages/2-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 3 — then do exactly these three and you'll be ready for the quiz: 1. Watch Crash Course #3 — Mean, Median, and Mode (group ①). 2. Read How to Calculate Standard Deviation (group ②). 3. Watch Boxplots are Awesome!!! (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.