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

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.