To calculate beta requires making a "what if" assumption about the true population parameter, where the "what-if" value is one that would cause the null hypothesis to be false.

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Beta, in hypothesis testing, is calculated under the assumption of a specific alternative hypothesis value, which inherently means assuming a situation where the null hypothesis is false. This is because beta represents the probability of a Type II error, which occurs when the null hypothesis is falsely accepted.

To Calculate Beta Requires Making a "What If" Assumption About