In: Statistics and Probability
In the book Business Research Methods, Donald R. Cooper and C. William Emory (1995) discuss a manager who wishes to compare the effectiveness of two methods for training new salespeople. The authors describe the situation as follows:
The company selects 22 sales trainees who are randomly divided into two equal experimental groups—one receives type A and the other type B training. The salespeople are then assigned and managed without regard to the training they have received. At the year’s end, the manager reviews the performances of salespeople in these groups and finds the following results:
A Group | B Group | |
Average Weekly Sales | x¯1x¯1 = $1,391 | x¯2x¯2 = $1,249 |
Standard Deviation | s1 = 201 | s2 = 265 |
(a) Set up the null and alternative hypotheses needed to attempt to establish that type A training results in higher mean weekly sales than does type B training.
H0: µA -
µB = versus Ha:
µA -
µB >
(b) Because different sales trainees are assigned to the two experimental groups, it is reasonable to believe that the two samples are independent. Assuming that the normality assumption holds, and using the equal variances procedure, test the hypotheses you set up in part a at level of significance .10, .05, .01 and .001. How much evidence is there that type A training produces results that are superior to those of type B? (Round your answer to 3 decimal places.)
t = |
(Click to select)Do not reject or Reject H0 with alpha equal to .10. |
(Click to select)Do not reject or Reject H0 with alpha equal to .05 |
(Click to select)Do not reject or Reject H0 with alpha equal to .01 |
(Click to select)Do not reject or Reject H0 with alpha equal to .001 |
(Click to select)Very strong,NoStrong, Weak, Extremely strong evidence that µA - µ B > 0 |
(c) Use the equal variances procedure to calculate a 95 percent confidence interval for the difference between the mean weekly sales obtained when type A training is used and the mean weekly sales obtained when type B training is used. Interpret this interval. (Round your answer to 2 decimal places.)
Confidence interval [, ]
a) H0: µA - µB = 0 versus Ha: µA - µB > 0
b)
t = 1.416 Reject H0 with alpha equal to .10.
t = 1.416 Do not reject with alpha equal to .05
t = 1.416 Do not reject with alpha equal to .01
t = 1.416 Do not reject with alpha equal to .001
Weak evidence that µA - µ B > 0
c)
point estimate of mean difference= | x1-x2 | = | 142.000 | ||
for 95 % CI & 20 df value of t= | = | 2.0860 | |||
margin of error E=t*std error = | 209.1927 | ||||
lower confidence bound=mean difference-margin of error = | -67.193 | ||||
Upper confidence bound=mean differnce +margin of error= | 351.193 |
Confidence interval =-67.19 ; 351.19