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Type I and Type II Errors in Hypothesis Testing
We reject the null hypothesis or do not reject the null hypothesis based on comparing the calculated test statistic to a specified possible value or values. The comparison values we choose are based on the level of significance selected.
The probability of a Type I error in testing a hypothesis is denoted by α, also known as the levelof significance of the test.
The probability of a Type II error is denoted by β.
The power ofa test is the probability of correctly rejecting the null. When more than one test statistic is available, we should prefer the most powerful, all else equal.
Type I and Type II Errors in Hypothesis Testing:all else equal.
Hypothesis Testing:Hypothesis Testing:Testing7 Making the economic or investmentdecision.
Optimal Price and Output in Perfect Competition:costcompetitive firm earns zero economic profit in the long run.
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