LS9 - Type I and Type II Errors

Question 1

Level Of Statistical Significance

Answer 1

The level at which the decision is made to reject the null hypothesis and accept the experimental hypothesis. It states how sure we can be that the IV is having an effect on the DV and this is not due to chance.

Question 2

Significance Levels

Answer 2

How certain we are that there is a real differnece between the two data sets and it isn’t due to chance.

Question 3

Probability

Answer 3

A measure of whether our results are due to chance or whether there is a real difference between the experimental and control conditions. If a real difference exists we can say the results are significant.

Question 4

Standard Significance Level

Answer 4

p<0.05 so a 5% signifiance level, meaning we are 95% certain that our results are showing a real difference between the control and experimental conditions and there is a 5% chance the relationship is a fluke.

Question 5

Why Do We Use A 5% Signifiance Level

Answer 5

It is not too strict or too lenient, it is a fair value of signifiance
It minimises the chances of making a type 1 or type 2 error

Question 6

When Is A Strict Significance Level Used?

Answer 6

11% may be ued when the findings are critical e.g. when testing the effect of drugs on humans, we must make sure that results are not due to fluke, as it can fatal.

Question 7

Type 1 Error

Answer 7

A Type 1 Error occurs if an investigator rejects a null hypothesis that is actually true in the population.