The higher the significance level used for testing a hypothesis, the higher is the probability of rejecting the null hypothesis when it is true.

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This is because a higher significance level means we are willing to tolerate a higher chance of making a Type I error (rejecting the null hypothesis when it is actually true), which increases the likelihood of rejecting the null hypothesis.

The Higher the Significance Level Used for Testing a Hypothesis