Inferential Statistics

Question 1

What do statistical tests show us

Answer 1

The stats tests calculate whether a result is significant using different levels of significance. For instance it would suggest whether the probability of the result is due to chance or whether we can have a confidence in the significance of the results obtained

Question 2

Different levels of significance

Answer 2

O.1% - highly significant - used in important research when the risk of chance must be minimised
1% - very significant - may be used when challenging previous research findings
5% - significant - conventional and accepted minimal level of significance used in psychology
10% - not significant but may be an effect - may be worth doing follow up studies

Question 3

The 5% level of significance

Answer 3

Means there is a 95% confidence that the result is significant and there is only a 5% probability that the results are due to chance
It strikes a balance between making a type 1 and type 2 error so is the best to use

Question 4

Type I error

Answer 4

False positive
You have rejected the null hypothesis when you should have accepted it. More likely to make the error with a 10% level of significance

Question 5

Type II error

Answer 5

False negative
You have accepted the null hypothesis when you should have rejected it
More likely to be made with a 1% level of significance

Question 6

Nominal Data

Answer 6

Worst kind of data
Categories/ labels
No individual scores they are gathered into a category
Eg yes or no, win or lose

Question 7

Ordinal data

Answer 7

Order and ranked position
It’s on a subjective scale and the gaps between scores are not equal
Eg 1st 2nd 3rd, sad neither happy

Question 8

Interval data

Answer 8

Best data
Fixed gaps between data, fixed intervals
Real measurements that can be plotted on a ruler
Gaps between scores are the same
Objective scores
Time (secs), height (cm)