Chapter 7: Inference For Numerical Data Flashcards

1
Q

When is the t-distribution used?

A

When the sample size is small and population standard deviation is unknown.

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2
Q

What are the conditions for using the t-distribution?

A

Independent observations and an approximately normal population.

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3
Q

What is paired data?

A

Data where observations are naturally matched, like before and after measurements.

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4
Q

What is the test statistic formula for a paired t-test?

A

T = (x̄_diff - 0) / (s_diff / √n)

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5
Q

What is the degrees of freedom for a paired t-test?

A

df = n - 1

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6
Q

What is the formula for a confidence interval using t-distribution?

A

x̄ ± t* × (s / √n)

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7
Q

When comparing two independent means, what test do you use?

A

Two-sample t-test.

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8
Q

What is the test statistic for two-sample t-test?

A

T = (x̄1 - x̄2) / sqrt(s1²/n1 + s2²/n2)

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9
Q

What are the hypotheses for a two-sample t-test?

A

H₀: μ₁ = μ₂ vs Hₐ: μ₁ ≠ μ₂

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10
Q

What is the formula for degrees of freedom in a two-sample t-test (simplified)?

A

df = min(n₁ - 1, n₂ - 1)

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11
Q

What is a Type I error?

A

Rejecting the null hypothesis when it is actually true.

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12
Q

What is a Type II error?

A

Failing to reject the null hypothesis when it is actually false.

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13
Q

What is the power of a test?

A

The probability of correctly rejecting a false null hypothesis (1 - β).

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14
Q

How can we increase the power of a test?

A

Increase sample size, reduce standard deviation, or raise α.

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15
Q

What is the effect size?

A

The magnitude of the difference you aim to detect.

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16
Q

What happens to power when sample size increases?

A

Power increases.

17
Q

What is the margin of error in a confidence interval?

A

ME = t* × SE

18
Q

When do we use a paired t-test?

A

When comparing means from the same group at different times or matched groups.

19
Q

What distribution has thicker tails: t or normal?

A

The t-distribution.

20
Q

What does a large p-value mean in hypothesis testing?

A

There is not enough evidence to reject the null hypothesis.