Are the following statements true or false?
(a) In hypothesis testing the null hypothesis can never be proved to be correct.
(b) For a given data set a two-sided confidence interval for a parameter with a confidence level 99% is shorter than a two-sided confidence interval for the parameter with a confidence level 95%.
(c) A statistical proof that a statement is true is achieved when the null hypothesis that the statement is false is rejected.
(d) A hypothesis test addresses the question of whether or not there is sufficient evidence to establish that the null hypothesis is false.
(e) A p-value between 1% and 10% should be interpreted as implying that there is some evidence that the null hypothesis is false, but that the evidence is not overwhelming.
(f) z-intervals are sometimes referred to as large sample intervals.
(g) If the p-value is 0.39 the null hypothesis is accepted at size or = 0.05.