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Null hypothesis:
States there is no difference between conditions (e.g. Gender does not effect driving ability).

Alternative hypothesis:
states there is a difference between conditions (e.g. Gender does effect driving ability).

Type 1 error:
if we reject the null in favour of the alternative even though the findings are actually due to chance.

Type 2 error:
We might retain the null hypothesis even though the alternative is actually correct.

A statistical test:
 Various formulae that enable researchers
 To analyse and compare the data produced in their studies. A statistical test produces a statistic that can be assessed, using tables of significance to see if the data fit (or do not fit) the hypothesis.


Level of significance
is not given assume 0.05. they may ask you to work to a different level of significance.

