Lecture 1 - Hypothesis testing Flashcards

1
Q

What is a Q-Q plot?

A

A quantile-quantile plot, i.e. a probability plot.
It is a graph that compares two probability distributions by plotting their quantiles against each other.

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2
Q

You are tesing whether hormone levels differ between boys and girls. Describe the null and alternative hypothesis.

A
  • Null: there is no difference in hormone levels between boys and girls.
  • Alternative: there is a difference in hormone levels between boys and girls.
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3
Q

Which two values are important to take into consideration when determining whether to reject H0 and accept Ha or to accept H0 and reject Ha?

A
  • p-value: the probability of finding the observed results when the null hypothesis is true.
  • significance level: the probability of rejecting the null hypothesis when the null hypothesis is actually true.
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4
Q

How are the p-value and significance level used to determine whether to accept or reject H0?

A
  • if p-value is higher than the signifcance level (e.g. p-value of 0.1 compared to significance level of 0.05), accept H0.
  • if p-value is lower than the significance level (e.g. p-value of 0.001 compared to significance level of 0.05), reject H0.
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5
Q

What is a type I and type II error?

A
  • Type I error: mistakenly rejecting H0 while it is actually true.
  • Type II error: mistakenly accepting H0 while it is actually false.
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6
Q

Complete the sentences.

  • The probability of a type I error is equal to …
  • The probability of a type II error is denoted as …
A
  • The probability of a type I error is equal to significance level α.
  • The probability of a type II error is denoted as β.
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6
Q

Independent sample t-test
What is it used for?

A

Used for comparing the means of two independent population means.

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6
Q

Independent sample t-test
What assumptions need to be met?

A
  • Outcome in both groups is normally distributed.
  • Variances (SD^2) of both groups are equal
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7
Q

Independent sample t-test
* What solutions is there if the outcomes in both groups are not normally distributed?
* How can equal variances be assumed?

A
  • Either transform the outcome or use a non-parametric test (Mann-Whitney test).
  • Levene’s test can be used. If the p-value of Levene’s test is ≥0.05, equal variances can be assumed.
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8
Q

Paired sample t-test
What is it used for?

A

Used for comparing the means of two times measured, paired variables (e.g. baseline and follow-up measurement).

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9
Q

Paired sample t-test
What assumptions need to be met?

A
  • The mean difference between the two measurements are normally distributed.
  • Variances of both groups are equal
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10
Q

Paired sample t-test
What solution is there if the mean difference between two measurements are not normally distributed?

A

Transform the outcome or use a non-parametric test (Wilcoxon signed rank test).

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11
Q

If α decreases, β will increase and vice versa. Ideally, you want both α and β to be as small as possible. How can you achieve the latter?

A

By increasing the sample size n.

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12
Q

What is needed to determine the sample size n?

A
  • The primary outcome measure
  • The statistical test: the expected outcomes (means, SDs), significance level (α), and the desired power (1-β) of the study.

Standard choices: α = 0.05, 1-β = 0.8 or 0.9

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