Setting the significance level cutoff at .10 instead of the more usual .05 increases the likelihood of A. a Type I error. B. accepting the null hypothesis when, in fact, it is false. C. a Type II error. D. failing to reject the null hypothesis.
As we are increasing the level of significance here from 0.05 to 0.1, therefore we would be more easily able to reject the null hypothesis here. For null hypothesis to be rejected, we want p-value of the test to be less than the level of signficance, therefore lesser the value of level of significance, easier it is for the null hypothesis to get rejected. As it is easier for null hypothesis to be rejected, therefore B,D are incorrect here.
Type I error is the probability of rejecting a true null hypothesis, as the rejection of null hypothesis has become more likely with a greater level of significance, therefore A is the correct answer here.
Type II error is not rejecting but retaining the null hypothesis here. therefore C is incorrect here.
Therefore A is the correct answer here.
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