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Indicate whether the following statement is true or false. In hypothesis testing, the p-value should always...

Indicate whether the following statement is true or false. In hypothesis testing, the p-value should always be larger than the selected level of significance.

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The p-value is the probability of obtaining results as extreme as the observed results of a statistical hypothesis test under the null hypothesis. Less is the value of this probability, strong is the evidence regarding alternative hypothesis.

on the other hand significance level is the probability of rejecting null when the null hypothesis is true.

p-value is calculated independently of the given level of significance. If it becomes less than the significance level then the probability is quite low to get atleast the observed result when null is true. Hence it indicates the alternative to be true.Therefore we reject the null.

Similarly if p-value becomes greater than the significance level then we consider it to be happened under null with a significant probability. Hence we can not reject the null.

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