Week 5 — Readings & Resources · Probability Foundations
Course: Introduction to Statistics (18-week generic edition)
Objective covered: Objective 4 — Apply probability rules, conditional probability, and random variables to quantify chance (this week: the probability-rules and conditional-probability portion).
Your primary reading is Chapter 5 (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 three 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 what probability is (the long run, sample spaces) → ② the rules — complement, addition, multiplication, and independence → ③ conditional probability & two-way tables.
A habit to start now: every time one of these resources hands you a probability, run the week's two reflexes — is it between 0 and 1? and can I say it out loud as a long-run statement?
① What Probability Is · Sample Spaces & the Long Run
Maps to Chapter 5, Sections 1–2 and Lecture Segments 2–3. The motto to carry: probability is a long-run promise, not a short-run guarantee.
Reading — Probability (Math is Fun)
🔗 https://www.mathsisfun.com/data/probability.html
Why it's assigned: the friendliest possible tour of the basics — the favorable-over-total recipe, the 0-to-1 scale, and the sample-space vocabulary (experiment, outcome, event) — with dice and card examples that mirror ours.
⏱ ~7 min
Video — Probability explained | Independent and dependent events | Probability and Statistics | Khan Academy (video, ~8 min, captioned)
🔗 https://www.youtube.com/watch?v=uzkc-qNVoOk
Why it earns the click: the classic first walk through equally likely outcomes with coins and dice — watch how every probability is built as favorable ÷ total, exactly the Segment 3 recipe.
② The Rules · Complement, Addition, Multiplication & Independence
Maps to Chapter 5, Sections 3–5 and Lecture Segments 4–5. The hooks: "OR adds — then subtracts the overlap" and "AND multiplies — when trials don't talk."
Reading — Mutually Exclusive Events (Math is Fun)
🔗 https://www.mathsisfun.com/data/probability-events-mutually-exclusive.html
Why it's assigned: the addition rules in one place — plain adding when events can't both happen, and the subtract-the-overlap version when they can — with a card example that parallels our queen-of-hearts double-count.
⏱ ~6 min
Reading — Probability: Independent Events (Math is Fun)
🔗 https://www.mathsisfun.com/data/probability-events-independent.html
Why it's assigned: the multiplication rule for independent events, plus the page's blunt warning about believing a coin is "due" — the gambler's fallacy, named and dismantled.
⏱ ~7 min
Video — Probability Part 1: Rules and Patterns: Crash Course Statistics #13 (video, ~13 min, captioned)
🔗 https://www.youtube.com/watch?v=OyddY7DlV58
Why it earns the click: the liveliest tour of the whole rule set — addition, multiplication, and the difference between empirical and theoretical probability — in one sitting; ideal the night before the quiz.
③ Conditional Probability · Two-Way Tables & "Given"
Maps to Chapter 5, Section 6 and Lecture Segment 6. The move: shrink your world to B, then re-count — and never confuse P(A | B) with P(B | A).
Reading — Conditional Probability (Math is Fun)
🔗 https://www.mathsisfun.com/data/probability-events-conditional.html
Why it's assigned: builds "given" from scratch with dependent events (drawing without replacement), introduces the P(A|B) notation, and shows the tree-diagram picture some students find clearer than tables.
⏱ ~8 min
Video — An Introduction to Conditional Probability (jbstatistics) (video, ~7 min, captioned)
🔗 https://www.youtube.com/watch?v=bgCMjHzXTXs
Why it earns the click: calm, precise, and definition-first — the formula P(A|B) = P(A and B)/P(B) worked on concrete examples, exactly at this course's depth.
Video — Conditional Probabilities, Clearly Explained!!! (StatQuest with Josh Starmer) (video, ~7 min, captioned)
🔗 https://www.youtube.com/watch?v=_IgyaD7vOOA
Why it earns the click: conditional probability computed straight from a two-way table of counts — the shrink-the-world move from our factory example, drawn out cell by cell.
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 3 (Probability Topics) covers this week end to end — terminology, independent and mutually exclusive events, the addition and multiplication rules, and contingency (two-way) tables.
🔗 https://openstax.org/books/introductory-statistics-2e/pages/3-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 (≈20 min total)
In a hurry? You've read Chapter 5 — then do exactly these three and you'll be ready for the quiz:
1. Read Mutually Exclusive Events (group ②).
2. Watch Crash Course #13 — Probability Part 1: Rules and Patterns (group ②).
3. Watch Conditional Probabilities, Clearly Explained!!! (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.