Which of the following statements about hypothesis testing is least accurate? A) The null hypothesis is a statement about the value of a population parameter. B) A Type II error is failing to reject a false null hypothesis. C) If the alternative hypothesis is Ha: µ > µ0, a two-tailed test is appropriate. D) A Type I error is rejecting the null hypothesis when it is actually true
C, should be greater than or equal to
actually it should be different than, no equality in the alternative, equality in the null.
Ok thanks. When I did this I read the question incorrectly. Hate it when that happens.
Whenever you find a A good approach to take is “least accurate” type question, cross out the “least accurate” and replace it with “False”. It helps to keep things straight.