BUSI 3301 – Business Statistics
QUESTION 1
# 9 Temperature’s Effect on Chemical Process: application problem on the completely randomized design.
To study the effect of temperature on yield in a chemical process, five batches were produced at each of three temperature levels. The results follow. Construct an analysis of variance table. Use a .05 level of significance to test whether the temperature level has an effect on the mean yield of the process.
Temperature
50o C 60o C 700 C
34 30 23
24 31 28
36 34 28
39 23 30
32 27 31
Your Answer:
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QUESTION 2
#15 Testing Chemical Process: application problem on the multiple comparison procedures.
To test whether the mean time needed to mix a batch of material is the same for machines produced by three manufacturers, the Jacobs Chemical Company obtained the following data on the time (in minutes) needed to mix the material.
Manufacturer
1
2
3
20
28
20
26
26
19
24
31
23
22
27
22
1. Use these data to test whether the population mean times for mixing a batch of material differ for the three manufacturers. Use a = .05.
2. At the a = .05 level of significance, use Fisher’s LSD procedure to test for the equality of the means for manufacturers 1 and 3. What conclusion can you draw after carrying out this test?
Your Answer:
QUESTION 3:
Gender Differences in Raise or Promotion Expectations. The Adecco Workplace Insights Survey sampled men and women workers and asked if they expected to get a raise or promotion this year. Suppose the survey sampled 200 men and 200 women. If 104 of the men replied Yes and 74 of the women replied Yes, are the results statistically significant in that you can conclude a greater proportion of men are expecting to get a raise or a promotion this year?
1. State the hypothesis test in terms of the population proportion of men and the population proportion of women.
2. What is the sample proportion for men? For women?
3. Use a .01 level of significance. What is the p-value and what is your conclusion?
QUESTION 4
Q2: Given the following data.
xi:
3
12
6
20
14
yi:
55
40
55
10
15
The estimated regression equation for these data is ý = 68 – 3x.
1. Compute SSE, SST, and SSR using equations (14.8), (14.9) and (14.10).
2. Compute the coefficient of determination r2. Comment on the goodness of fit.