Decision Making

Question 1

What does the ‘significance level’ refer to in hypothesis testing?

Answer 1

represents the threshold for deciding whether to reject the null hypothesis

Question 2

What is a Type I error and what is another name for it?

Answer 2

-False positive
when the null is true (there is no effect), but we reject it anyway
-evidence leads to wrong conclucion

Question 3

What is a Type II error and what is another name for it?

Answer 3

-False negative
Null is false(there is an affect), yet we fail to reject it
not enough evidence to conclude, too few observations, pop large var

Question 4

What type of error occurs if H0 is False but we fail to reject it?

Answer 4

type 2 error

Question 5

What type of error occurs if HA is True but we do reject it?

Answer 5

type 2

Question 6

Explain why using 𝛼 = 0.05 as a strict cut-off for significance is problematic

Answer 6

-relies on sample size and samples can be manipulated to create a higher

Question 7

What should determine the value we use for our significance level of a hypothesis test?

Answer 7

Fischer wanted the signifiance level to be adjusted to the seriousness of getting a wrong conclcuon, 0.05 just has been universally accepted.

Question 8

Explain in your own words what is meant by the following phrase: “Over time it appears the p-value has become a gatekeeper for whether work is publishable.”

Answer 8

Studies with p-values above this threshold are frequently dismissed as “insignificant,” even if their results might have practical or scientific value