type 1 and 2 errors

Question 1

type 1

Answer 1

Type I Error (False Positive)
You reject the null hypothesis, but it’s actually true.

You conclude there is an effect, but there isn’t.

Reality: Null is true

Decision: Incorrectly reject the null hypothesis

Common cause: Significance level (α) is too high (e.g. 0.10 instead of 0.05)

Example: Concluding a therapy works when it actually doesn’t

Question 2

type 2

Answer 2

Type II Error (False Negative)

You fail to reject the null hypothesis, but it’s actually false.

You conclude there is no effect, but there is one.

Reality: Null is false

Decision: Incorrectly accept or fail to reject the null hypothesis

Common cause: Low statistical power, often due to small sample size

Example: Concluding a therapy doesn’t work when it actually does