RM - Type 1/2 Errors

Question 1

Type 1 Error Definition

Answer 1

When the researcher has used a lenient P value. Researcher thinks the results are significant when they’re actually due to chance/error. So they wrongly accept the experimental hypothesis and wrongly reject null hypothesis

Question 2

How to check for a type 1 error?

Answer 2

Compare the calculated value to a critical value from a more stringent p value. If results are still significant, type 1 error not made. If results are now not significant, there’s a chance of a Type 1 error.

Question 3

Why do we use a 5% sig level?

Answer 3

Strikes a balance between risk of making a type 1 and type 2 error. Conventional significance level.

Question 4

Type 2 Error Definition

Answer 4

When the researcher has used a stringent P value. Researcher thinks the results are significant when they’re actually due to chance/error. So they wrongly accept the null hypothesis and wrongly reject experimental hypothesis

Question 5

How to check for a type 2 error?

Answer 5

Compare the calculated value to a critical value from a more lenient p value. If results are still not significant, type 2 error not made. If results are now significant, there’s a chance of a Type 1 error.