In: Statistics and Probability
Which of the following is TRUE?
A) The statement of the null hypothesis never contains an equality.
B) The alternative hypothesis represents the conclusion for which evidence is sought.
C) The computed test statistic is also known as the critical value.
D) An increase in the risk of type I error also increases the risk of a type II error.
Statement B is True.
The alternative hypothesis is a what the research asks us to do, to either prove that a population parameter, represented by a sample statistic is greater than, lesser than or not equal to a certain value. We use the sample and run tests to come to a conclusion whether the research is question is True or if we do not have sufficient evidence it is true.
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(A) Statement A is false as the null hypothesis has to have the sign of equality always (= , , )
(C) Statement C is false as the test statistic and the critical value are 2 different quantities found by different methods. The critical value is used to define the rejection region of the test statistic.
(D) An increase in the probability of a Type I error to increase the power of the test which is = , where is the probability of the Type II error. Therefore as power increases, decreases.
Therefore Increasing the probability of a Type I error reduces the probability of a Type II error.
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