Review & Spaced Repetition

How to use this page: Work through each question below *without* peeking at the notes first. Only look back at the topic page when you're truly stuck. Then check your session off in the spaced-review calendar.

Central Tendency (Mean / Median / Mode)

1. 1.What is the formula for the mean, and why can it be misleading for income data?
2. 2.When is the median a better measure of centre than the mean? Give a real-world example.
3. 3.What kind of data is the mode most useful for, and why?
4. 4.If a single billionaire is added to a salary dataset, which measure of central tendency changes the most — and which stays most stable?

[Lecture notes.md]

Spread (Variance & Standard Deviation)

1. 1.Why do we *square* the deviations when calculating variance instead of just averaging them directly?
2. 2.What are the units of variance compared to the units of the original data?
3. 3.What does it mean when σ = 0? What does that tell you about the dataset?
4. 4.How does standard deviation improve on variance in terms of interpretability?
5. 5.In one sentence, what do both variance and standard deviation measure?

[Lecture notes.md]

Normal Distribution

1. 1.State the 68-95-99.7 rule. What percentage of data falls within mean ± 2σ?
2. 2.What is the approximate probability of a value falling *outside* mean ± 2σ in a normal distribution?
3. 3.What happens to the shape of the bell curve as σ increases?
4. 4.In a perfectly normal distribution, what is the relationship between the mean, median, and mode?
5. 5.Name two real-world contexts where the normal distribution commonly appears.

[Lecture notes.md]

Correlation vs Causation

1. 1.What is the range of the correlation coefficient *r*, and what do the extremes mean?
2. 2.What does r = 0 tell you — and what does it *not* tell you?
3. 3.Explain the ice-cream/drowning example. What statistical concept does it illustrate?
4. 4.What are two common reasons a correlation might *not* indicate causation?

[Lecture notes.md]

Use this calendar to space out your review sessions. Each session should focus on the questions above — close the notes, answer aloud or in writing, then check. [Lecture notes.md]

• Feynman check: After each session, try to explain the concept to an imaginary friend in plain English. If you stumble, that's your weak spot — revisit that topic page.
• Interleave: Don't block all of one topic at once. Mix central tendency questions with spread questions to strengthen retrieval.
• Prioritise struggle: Spend *more* time on questions you got wrong, not the ones you already know. [Lecture notes.md]

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