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* **Significance Level (Alpha):** This is the threshold we set before we even collect any data. It's the probability of rejecting the null hypothesis when it is actually true (a Type I error). Think of it as the maximum risk we're willing to take of being wrong. Typically, the significance level is set at 0.05 (5%), which means we're willing to accept a 5% chance of incorrectly rejecting the null hypothesis. This value is used as a benchmark to assess the strength of the evidence against the null hypothesis. Choosing an appropriate significance level is an important step in designing a **hypothesis test** because it affects the power of the test and the probability of making a Type II error (failing to reject the null hypothesis when it is false).
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