Type I and Type II Errors

Question 1

Define type I error

Answer 1

When the researcher has used a lenient P value. The researcher thinks the results are significant when they are actually due to chance. So they wrongly accept the alternative hypothesis and wrongly reject the null.

Question 2

Define Type II error

Answer 2

When the researcher uses a stringent P value. They sinks the results are not significant when they could be significant. They wrongly accept the null hypothesis and wrongly reject the alternative.

Question 3

Why do psychologists use 5% significance level?

Answer 3

It strikes a balance between the risk of making a type 1 and type 2 error. Its a conventional significance level.

Question 4

How to check for a type 1 error?

Answer 4

1) Go to a more strict significance level and check the calculated against the critical value

2) If results are still significant, not a type 1 error

Question 5

How to check for a type 2 error?

Answer 5

1) Go to a more lenient significance level and check calculated against critical value

2) If still not significant, no type 2 error