In our example, we fail to reject the null hypothesis at the 5% level.

The idea is that if the results don't reject the null hypothesis, then you aren't finding anything new or surprising.

Therefore, we can reject the null hypothesis, which states that the two events are independent.

Hence, we fail to reject the null hypothesis at the 5% level.

Hence the result provides enough evidence to reject the hypothesis of 'no effect'.

The user may reject the null hypothesis if is too small.

They do not reject the hypothesis that players choose their strategies optimally.

Thus the test provides strong evidence to reject the null hypothesis of no treatment effect.

A positive or statistically significant result is one which rejects the null hypothesis.

On the other hand, if the control culture does not die, then the researcher cannot reject the hypothesis that the drug is efficacious.