| Tag | Value |
|---|---|
| file | Inferential_Statistics_vufsw-typeiierror-1173-en_vufsw-typeiierror-1173-en |
| name | vufsw-typeiierror-1173-en |
| section | inferential statistics/nhst/statistical errors/type II error |
| type | schoice |
| solution | FALSE, TRUE, FALSE, FALSE |
| Type | conceptual |
| Program | NA |
| Language | English |
| Level | statistical reasoning |
A researcher is interested in the difference in study results between students who are optimistic versus students who are pessimistic. Suppose that the researcher does not find a significant difference between the two groups of students, while in the population a difference actually exists.
What is going on?
A type II error is made.
In statistical hypothesis testing, a type I error is the rejection of a
true null hypothesis (also known as a “false positive” finding), while a
type II error is failing to reject a false null hypothesis (also known
as a “false negative” finding).
More simply stated, a type I error is to falsely infer the existence of
something that is not there, while a type II error is to falsely infer
the absence of something that is present.
M&T Basics of quantitative research
Basics of quantitative research
M&T Hypothesis testing: means
Default value