Type 1 errors | Inferential statistics | Probability and Statistics | Khan Academy

What defines a Type I error in hypothesis testing?

• Accepting the null hypothesis when it is false.

• Rejecting the null hypothesis when it is true.

• Accepting the alternative hypothesis when it is false.

• Rejecting the alternative hypothesis when it is true.

What is the initial assumption made about the null hypothesis (H0) in hypothesis testing?

• It is always false.

• It is always true.

• It is neither true nor false.

• Its truthfulness is irrelevant.

When is the null hypothesis typically rejected based on an observed statistic?

• When the probability of observing such a statistic (or more extreme) is high.

• When the probability of observing such a statistic (or more extreme) is exactly 50%.

• When the probability of observing such a statistic (or more extreme) is below a set threshold.

• When the observed statistic is exactly equal to the mean of the assumed distribution.

If the null hypothesis is true, and an observed statistic has a 0.5% probability of occurring (or being more extreme), what is the probability of making a Type I error if the threshold for rejection is 1%?

• 1%

• 0.5%

• 99%

• 5%