You chose whether or ot to reject the null hypothesis. Or you repeat the experiment.
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If you already have your p-value, compare it with 0.05. If the p-value is less than an alpha of 0.05, the t-test is significant. If it is above 0.05, the t-test is not significant.
Rejecting or Failing to reject the Null Hypothesis (Ho) depends of the P-Value. Generally, the P-value (probability( Observation | Ho ) ) is around .05, thus minimizing the Type 1 error rate. If the P-value < Alpha , you would reject the Ho, and instead believe the Ha (Alternative Hypothesis), and if the P-value > Alpha, you would Fail to reject the Ho because there is not enough evidence to believe the Ha.
you do not need to reject a null hypothesis. If you don not that means "we retain the null hypothesis." we retain the null hypothesis when the p-value is large but you have to compare the p-values with alpha levels of .01,.1, and .05 (most common alpha levels). If p-value is above alpha levels then we fail to reject the null hypothesis. retaining the null hypothesis means that we have evidence that something is going to occur (depending on the question)
Yes, if p=1 that means an event is 100% certain to happen. For example, p value for picking a day of the week in the Enlish Language that ends in AY is 1 or 100%.P values can be anywhere between 0 and 1 inclusive. For for an event, E, we can always say 0< or equal to P(E)< or equal to 1.
It is 12*P*P*P whose value will depend on the value of P.