Given the alternative hypothesis that a new process is better than the old one, the Type I Error is to conclude that:

    Given the alternative hypothesis that a new process is better than the old one, the Type I Error is to conclude that:

       A. the old process is as good or better when it is not            

       B. the old process is better when it is

       C. the new process is better when it is not

       D. the new process is as good or better when it is 

    If the number of observations (n) is increased to 2n, the level of significance (ALPHA) is:

       A. increased    

       B. unaffected    

       C. decreased

    The level of significance is (check all that apply):

       A. the probability of rejecting the null hypothesis when the null hypothesis is true.

       B. the magnitude of the sample size.

       C. symbolized by the Greek letter ALPHA.

       D. none of the above.

  A result was said to be statistically significant at the 5% level. This means:

            A. the null hypothesis is probably wrong

            B. the result would be unexpected if the null hypothesis were true

            C. the null hypothesis is probably true

            D. none of the above.

   In hypothesis testing, what is the function of a critical value that is taken from the tables?

       a. It is equal to the calculated statistic from the observed data.

       b. It is the point where the decision changes from reject to fail to reject.

       c. It is the center of the distribution of X's.

       d. It is a point which is 1 standard deviation away from the mean.

  True or False? If False, correct it.

          If we would reject a null hypothesis at the 5% level, we would also reject it at the 1% level.

       False - A result may be significant at the 5% level, but not at the 1% level.

  True or False? If False, correct it.

          One can never prove the truth of a statistical (null) hypothesis. One can only tend to discount it.