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Should you reject or fail to reject the null hypothesis?
After you perform a hypothesis test, there are only two possible outcomes. When your p-value is less than or equal to your significance level, you reject the null hypothesis. When your p-value is greater than your significance level, you fail to reject the null hypothesis.
Do you reject the null or accept alternative?
Rejecting or failing to reject the null hypothesis If our statistical analysis shows that the significance level is below the cut-off value we have set (e.g., either 0.05 or 0.01), we reject the null hypothesis and accept the alternative hypothesis.
How do you know if you reject or accept null hypothesis?
If the P-value is less than (or equal to) , then the null hypothesis is rejected in favor of the alternative hypothesis. And, if the P-value is greater than , then the null hypothesis is not rejected.
Do we always want to reject the null hypothesis?
It is not taken for granted that the null is always to be rejected. In model fit testing, the null is usually that the model fits well, and that is something desirable that we would hate to reject.
What to do if fail to reject the null hypothesis?
We do not know if the null is true or if it is false. If the null is false and we reject it, then we made the correct decision. If the null hypothesis is true and we fail to reject it, then we made the correct decision.
Does failing to reject null mean null is true?
In a similar way, a failure to reject the null hypothesis in a significance test does not mean that the null hypothesis is true. It only means that the scientist was unable to provide enough evidence for the alternative hypothesis.
When to reject or accept null hypothesis?
If the sample does not support the null hypothesis, we reject it on the probability basis and accept the alternative hypothesis. If the sample does not oppose the hypothesis, the hypothesis is accepted.
Do we reject or accept the null hypothesis?
Rejecting or failing to reject the null hypothesis. Alternatively, if the significance level is above the cut-off value, we fail to reject the null hypothesis and cannot accept the alternative hypothesis. You should note that you cannot accept the null hypothesis, but only find evidence against it.
What is the reason of a null hypothesis being rejected?
In the significance testing approach of Ronald Fisher, a null hypothesis is rejected if the observed data is significantly unlikely to have occurred if the null hypothesis were true. In this case, the null hypothesis is rejected and an alternative hypothesis is accepted in its place. If the data is consistent with the null hypothesis statistically possibly true, then the null hypothesis is not rejected.