MAT300 Homework Complete Solution
MAT 300
All calculations and relevant Minitab output must be included to receive full credit. Be sure to word-process your solutions and copy and paste the appropriate outputs from Minitab. Show all steps used in arriving at the final answers. Incomplete solutions will receive partial credit. This exam covers content from Modules One through Three.
(1) Consider the GASTURBINE data set and corresponding output from Minitab. Note that all tests should be performed at the α = 0.05 level. Use the complete data set in your analysis. The first 10 observations are given for illustrative purposes. Complete parts a) through f) below.
ENGINE |
SHAFTS |
RPM |
CPRATIO |
INLET-TEMP |
EXH-TEMP |
AIRFLOW |
POWER |
HEATRATE |
Traditional |
1 |
27245 |
9.2 |
1134 |
602 |
7 |
1630 |
14622 |
Traditional |
1 |
14000 |
12.2 |
950 |
446 |
15 |
2726 |
13196 |
Traditional |
1 |
17384 |
14.8 |
1149 |
537 |
20 |
5247 |
11948 |
Traditional |
1 |
11085 |
11.8 |
1024 |
478 |
27 |
6726 |
11289 |
Traditional |
1 |
14045 |
13.2 |
1149 |
553 |
29 |
7726 |
11964 |
Traditional |
1 |
6211 |
15.7 |
1172 |
517 |
176 |
52600 |
10526 |
Traditional |
1 |
6210 |
17.4 |
1177 |
510 |
193 |
57500 |
10387 |
Traditional |
1 |
3600 |
13.5 |
1146 |
503 |
315 |
89600 |
10592 |
Traditional |
1 |
3000 |
15.1 |
1146 |
524 |
375 |
113700 |
10460 |
Traditional |
1 |
3000 |
15 |
1171 |
525 |
514 |
164300 |
10086 |
Regression Analysis: HEATRATE versus RPM, CPRATIO, ...
The regression equation is
HEATRATE = 14314 + 0.0806 RPM - 6.8 CPRATIO - 9.51 INLET-TEMP + 14.2 EXH-TEMP
- 2.55 AIRFLOW + 0.00426 POWER
Predictor Coef SE Coef T P
Constant 14314 1112 12.87 0.000
RPM 0.08058 0.01611 5.00 0.000
CPRATIO -6.78 30.38 -0.22 0.824
INLET-TEMP -9.507 1.529 -6.22 0.000
EXH-TEMP 14.155 3.469 4.08 0.000
AIRFLOW -2.553 1.746 -1.46 0.149
POWER 0.004257 0.004217 1.01 0.317
S = 458.757 R-Sq = 92.5% R-Sq(adj) = 91.7%
Analysis of Variance
Source DF SS MS F P
Regression 6 155269735 25878289 122.96 0.000
Residual Error 60 12627473 210458
Total 66 167897208
(2) Using the FLAG data set (first 10 observations given), fit a model that predicts COST based on DOTEST. Use the complete data set in your analysis. Show the relevant output from Minitab in your answer. The first 10 observations are given for informational purposes.
CONTRACT |
COST |
DOTEST |
STATUS |
1 |
1379.43 |
1386.29 |
1 |
2 |
134.03 |
85.71 |
1 |
3 |
202.33 |
248.89 |
0 |
4 |
397.12 |
467.49 |
0 |
5 |
158.54 |
117.72 |
1 |
6 |
1128.11 |
1008.91 |
1 |
7 |
400.33 |
472.98 |
1 |
8 |
581.64 |
785.39 |
0 |
9 |
353.96 |
370.02 |
0 |
10 |
138.71 |
174.25 |
0 |
Calculate a confidence and prediction interval for DOTEST = 100. Interpret the confidence and prediction intervals given in the output. Do you see any problems with the interpretation of the prediction interval in terms of what we are trying to predict? Why are confidence intervals always more narrow than prediction intervals?
(3) Consider the EXPRESS data set (first 10 observations given). Use the complete data set in your analysis. Show the relevant output from Minitab in your answers. The first 10 observations are given for illustrative purposes.
Weight |
Distance |
Cost |
5.9 |
47 |
2.6 |
3.2 |
145 |
3.9 |
4.4 |
202 |
8 |
6.6 |
160 |
9.2 |
0.75 |
280 |
4.4 |
0.7 |
80 |
1.5 |
6.5 |
240 |
14.5 |
4.5 |
53 |
1.9 |
0.6 |
100 |
1 |
7.5 |
190 |
14 |
(4) Consider the EXPRESS data set (first 10 observations given). Use the complete data set in your analysis. Show the relevant output from Minitab in your answers. The first 10 observations are given for illustrative purposes.
Weight |
Distance |
Cost |
5.9 |
47 |
2.6 |
3.2 |
145 |
3.9 |
4.4 |
202 |
8 |
6.6 |
160 |
9.2 |
0.75 |
280 |
4.4 |
0.7 |
80 |
1.5 |
6.5 |
240 |
14.5 |
4.5 |
53 |
1.9 |
0.6 |
100 |
1 |
7.5 |
190 |
14 |
MAT300 Homework Complete Solution
The slope coefficients tell us the change in the HEATRATE for unit change in the independent variable given other variables are at the sa...
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