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Topic 4.18Math AI HL16 flashcards

t & z tests, errors (HL only)

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Card 1 of 164.18.1
4.18.1
Question

What does the p-value of a hypothesis test measure?

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All Flashcards in Topic 4.18

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4.18.18 cards

Card 1concept
Question

What does the p-value of a hypothesis test measure?

Answer

The probability of getting data at least this extreme if H₀ were true. Small p = the data are surprising under H₀.

Card 2formula
Question

State the decision rule for a hypothesis test.

Answer

p < α → reject H₀; p ≥ α → fail to reject H₀ (α = significance level).

Card 3concept
Question

When do you use a z-test vs a t-test?

Answer

z-test when the population σ is known; t-test when σ is unknown (you only have the sample sd) — the usual case.

Card 4concept
Question

One-sample vs two-sample test?

Answer

One-sample: compare one group's mean to a fixed claimed value. Two-sample: compare two independent groups' means.

Card 5concept
Question

When is a test one-tailed vs two-tailed?

Answer

One-tailed for a directional H₁ (μ < or μ >); two-tailed for H₁: μ ≠ (a difference either way).

Card 6concept
Question

What is a paired (matched) t-test for?

Answer

When the same subjects are measured twice (before/after). Test the mean of the differences d: H₀: μ_d = 0.

Card 7concept
Question

Why must you never say you 'accept H₀'?

Answer

A test can only fail to find evidence against H₀ — absence of evidence isn't proof. Say 'do not reject H₀'.

Card 8concept
Question

Where do the final marks in an AI hypothesis-test question usually sit?

Answer

In the in-context conclusion — naming the real quantities (bottles, runners…), not just 'reject H₀'.

4.18.28 cards

Card 9concept
Question

What is a Type I error?

Answer

Rejecting H₀ when H₀ is actually true (a false alarm — concluding there's an effect when there isn't).

Card 10concept
Question

What is a Type II error?

Answer

Failing to reject H₀ when H₀ is actually false (a miss — concluding there's no effect when there is one).

Card 11formula
Question

What is P(Type I error)?

Answer

It equals the significance level α (e.g. 0.05). Computed from the H₀ distribution / critical region.

Card 12concept
Question

What is P(Type II error), and what do you need to compute it?

Answer

β = P(not rejecting H₀ | the alternative is true). You need a SPECIFIC alternative value, and you use that distribution.

Card 13concept
Question

What is a critical (rejection) region?

Answer

The set of extreme outcomes for which you reject H₀. α = P(landing in it when H₀ is true).

Card 14concept
Question

Which distribution gives α, and which gives β?

Answer

α comes from the H₀ distribution; β comes from the alternative (H₁) distribution.

Card 15concept
Question

How do Type I and Type II errors trade off?

Answer

Lowering α shrinks the critical region, which makes a Type II error more likely (β rises), and vice versa.

Card 16concept
Question

For X ~ B(20, 0.5), test H₁: p > 0.5, reject if X ≥ 15. What is P(Type I error)?

Answer

P(X ≥ 15 | p = 0.5) = 1 − P(X ≤ 14) ≈ 0.0207.

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IB Math AI HL Topic 4.18 Flashcards | t & z tests, errors (HL only) | Aimnova | Aimnova