Probability and Significance:
Null hypothesis –
Predicts that the IV will have no effect on the DV
i.e. the results are due to chance alone, also known as H0
Probability –
A number between 0 and 1
0: something will not happen
1: something will definitely happen
Inferential statistics –
Allow us to calculate the probability that results could have arisen by chance
Used to analyse data and tell us the p value
P Value –
The likelihood of getting the findings if H0 is true
Anything less that or equal to 0.05 is considered significant and not due to
chance
This is the level of significance: p≤0.05 (5%)
Type 1 errors –
Rejecting the null hypothesis when it is actually true (false positive)
At p≤0.05, there is one in twenty chance of making a type 1 error
Type 2 errors –
Accepting the null hypothesis that is in fact not true (false negative)
The likelihood of this is increased if the level of significance is too low
Null hypothesis –
Predicts that the IV will have no effect on the DV
i.e. the results are due to chance alone, also known as H0
Probability –
A number between 0 and 1
0: something will not happen
1: something will definitely happen
Inferential statistics –
Allow us to calculate the probability that results could have arisen by chance
Used to analyse data and tell us the p value
P Value –
The likelihood of getting the findings if H0 is true
Anything less that or equal to 0.05 is considered significant and not due to
chance
This is the level of significance: p≤0.05 (5%)
Type 1 errors –
Rejecting the null hypothesis when it is actually true (false positive)
At p≤0.05, there is one in twenty chance of making a type 1 error
Type 2 errors –
Accepting the null hypothesis that is in fact not true (false negative)
The likelihood of this is increased if the level of significance is too low
