Probability and Significance

What is a null hypothesis?

A statement that predicts no effect or relationship between variables

What is an experimental hypothesis?

Statement that predicts a relationship or effect of the IV on the DV in an experiment

Why are levels of significance used?

Helps researcher to decide whether the results of a study are likely to be due to chance or reflect a real effect

What does p=0.05 mean?

There is a 5% chance the results occurred by luck and a 95% confidence that the effect is real.

Helps to determine whether to accept or reject the null hypothesis

Why are levels of significance important?

- ensures scientific credibility, we don't want to claim there's an effect when there isn't one

- balances the risk of type I and type II errors

- makes psychological research more reliable and valid

What is a type I error?

false positive

What is a false positive error?

When the researcher has rejected the null hypothesis when they should have accepted it, and instead accepted the experimental hypothesis when they should have rejected it

How can a false positive error occur?

- the researcher chooses a lenient significance level e.g 10%

- the results show they have a significant finding

- however, the research isn't tightly controlled and the results are due to chance

- false positive, rejected null hypothesis, accepted experimental hypothesis

What is a type II error?

false negative

What is a false negative error?

Researcher accepted the null hypothesis when they should have rejected it

How can a false negative error occur?

- researcher chooses a stringent significance level e.g 1%

- results show the researcher doesn't have a significant finding

- however, research is tightly controlled and the researcher overestimated chance

- false negative, accepted null hypothesis, rejected experimental hypothesis