MGMT2263
Worksheet #3
1)
A builder conducted a study in a major city in which
the city was divided into different regions. One of the regions had a higher
percentage of senior citizens than other regions of the city. He was concerned
that the age standard deviation in this region might be less than in the
others. The sample size of this region is 16 and the age standard deviation is
5.3 years. In another region chosen at random, the sample size is 13 and the
age standard deviation is 7.2 years. Based on this evidence, is the age
standard deviation in the first region significantly less than that of the
second region? Test at a 5% level of significance.
(F = 1.8455; conclude the standard deviation for the region with the high percentage of seniors is not significantly less than that of the other region)
2) Sales from two stores were gathered. Analysis of the data indicated both samples were normal. The summary statistics from the stores are:
|
|
Sample size |
Mean |
Std. Dev. |
|
Store 1 |
9 |
45 |
4.1 |
|
Store 2 |
10 |
48 |
9.2 |
Is there any significant difference in the standard deviations of the stores’ sales? Test at a 5% level of significance. (F = 5.0351; conclude the standard deviations are not equal)
3) A manufacturer is conducting a test of the tensile strengths of two types of copper coils. The summary statistics are:
|
|
Sample size |
Mean |
Std. Dev. |
|
Coil A |
9 |
118 |
17 |
|
Coil B |
16 |
143 |
24 |
The tensile strengths are approximately normally distributed. Is there any significant difference in the average strengths of the two types? Test at a 5% level of significance. (t = 2.7496; conclude the average strengths of the two types are not equal)
4) Is there a level of significance between 1% and 10% in which the opposite verdict would have been reached? (if the level of significance were set at 1%, the critical value would be 2.807 and the opposite conclusion would have been reached)
5) Construct a 95% confidence interval of the mean difference in tensile strengths of the two types of coil. What conclusion would you reach based on the results of the confidence interval? (6.1881 < mB - mA < 43.8119; we would reject Ho since the hypothesized difference of 0 does not fall in the confidence interval)
6) Let us return to the data from question 2 and test if there is any significant difference in the average sales of the 2 stores. Do not assume a level of significance. (t = -0.9333; p-value > 10%; conclude no significant difference in average sales of the 2 stores)
7) A business magazine compared bonuses for 10 executives for the years 2006 and 2007. These were the results (in thousands of dollars):
|
CEO |
2006 Bonus |
2007 Bonus |
|
#1 |
195 |
196 |
|
#2 |
183 |
160 |
|
#3 |
208 |
220 |
|
#4 |
190 |
195 |
|
#5 |
220 |
200 |
|
#6 |
235 |
250 |
|
#7 |
175 |
180 |
|
#8 |
150 |
145 |
|
#9 |
245 |
240 |
|
#10 |
210 |
230 |
Analysis of the data indicated they are normally distributed. Is there any significant difference in the average bonuses of the two years? Test at 5%.
(t = -0.1119; conclude there is no significant difference between the two years)
8) Construct a 95% confidence of the difference between the two years. Round the limits to the nearest hundred. Interpret the interval. Why would the same conclusion be reached? (-10,600 < m2006 - m2007 < 9,600; we would not reject Ho since the hypothesized difference of 0 falls in the confidence interval)
9) Suppose a level of significance had not been chosen. Why would the same conclusion be reached? (p-value > 10%; this provides strong support for Ho)
10) A law firm wants to know if there is a difference in the number of typing mistakes made by two secretaries in the firm. Each secretary was given 5 randomly selected documents to type. The results were:
|
Secretary A |
3 |
5 |
4 |
2 |
0 |
|
Secretary B |
2 |
0 |
4 |
3 |
1 |
No assumptions about the normality of the data were made. Test at a 5%. level of significance. (p-value = 0.5476; no significant difference)
11) Two samples of light bulbs are taken from two different brands. The following table gives the life of bulbs from the samples:
|
Brand A |
1134 |
1255 |
1313 |
1012 |
1265 |
1375 |
1102 |
|
|
1107 |
1095 |
1401 |
1109 |
1150 |
|
|
|
Brand B |
1405 |
1251 |
1106 |
1384 |
1193 |
1208 |
1110 |
|
|
1290 |
1210 |
1198 |
1203 |
1295 |
1102 |
1185 |
No assumptions about the normality of the data were made. Is there any significant difference in how long the bulbs from the 2 brands last? Test at a 5% level of significance. (Z = -0.8487; no significant difference)
12) A psychologist conducts a seminar to increase a person’s self-esteem. A before-and-after test that measures a person’s self-esteem was given to nine randomly selected individuals. The results were:
|
|
#1 |
#2 |
#3 |
#4 |
#5 |
#6 |
#7 |
#8 |
#9 |
|
Before |
70 |
72 |
75 |
61 |
82 |
55 |
43 |
51 |
84 |
|
After |
74 |
88 |
71 |
62 |
89 |
58 |
41 |
63 |
80 |
No assumptions about the normality of the data were made. Is the seminar’s method effective? Test at a 5% level of significance. (T- = 12; conclude method not effective)
13) A company tried a new reporting system to see if it would reduce the amount of time per day its salespeople spent doing paperwork. Here were the results in minutes:
|
|
#1 |
#2 |
#3 |
#4 |
#5 |
#6 |
#7 |
#8 |
#9 |
#10 |
|
Before |
34 |
35 |
43 |
46 |
16 |
26 |
68 |
38 |
61 |
52 |
|
After |
31 |
31 |
44 |
44 |
15 |
28 |
63 |
39 |
63 |
54 |
|
|
#11 |
#12 |
#13 |
#14 |
#15 |
#16 |
#17 |
#18 |
#19 |
#20 |
|
Before |
42 |
19 |
20 |
26 |
40 |
51 |
24 |
29 |
48 |
19 |
|
After |
38 |
21 |
19 |
22 |
38 |
50 |
21 |
33 |
51 |
18 |
No assumptions about the normality of the data were made. Is the system effective? Test at a 5% level of significance. (Z = 1.064; conclude system is not effective)