For each question, state the response variable, factor, blocking factor(if any) at the beginning
of your answer.
Include software output with your submission for the questions require Minitab usage.
Question 1) Consider the following computer output.
Source DF
SS
MS
F
P-value
Factor
?
117.4
Error
Total
16
396.8
39.1
?
?
?
19 514.2
means?
(a) How many levels of the factor were used in this experiment?
(b) How many replicates did the experimenter use?
(c) Fill in the missing information in the ANOVA table. Use bounds for the
P-value.
(d) What conclusions can you draw about differences in the factor-level
Question 2) A paper in the Journal of the Association of Asphalt Paving Technologists (1990, Vol. 59) described an
experiment to determine the effect of air voids on percentage retained strength of asphalt. For purposes of the experiment, air
voids are controlled at three levels; low (2-4%), medium (4-6%), and high (6-8%). The data are shown in the following table.
Air Voids
Retained Strength (%)
Low
Medium
High
106 90 103 90 79 88 92 95
80 69 94 91 70 83 87 83
78 80 62 69 76 85 69 85
(a) Do the different levels of air voids significantly affect mean retained strength? Use a = 0.01 and compare it to the p-value
of the ANOVA table to make conclusions. The data file Example 13.13.csv is provided with the hw file on Canvas. Use
Minitab stat->ANOVA->OneWay. Then select appropriate variables for response and factor.
(b) Now, use Critical Value approach F test you performed in part (a).
(c) Analyze the residuals from this experiment.
(d) Manually calculate a 95% confidence interval on mean retained strength where there is a high level of air voids.
(e) Manually calculate 95% confidence interval on the difference in mean retained strength at the low and high levels of air
voids.
Question 3)”The Effect of Nozzle Design on the Stability and Performance of Turbulent Water Jets” (Fire Safety
Journal, August 1981, Vol. 4. described an experiment in which a shape measurement was determined for several different
nozzle types at different levels of jet efflux velocity. Interest in this experiment focuses primarily on nozzle type, and velocity
is a nuisance factor. The data are as follows:
Jet Efflux Velocity (m/s)
Nozzle Type 11.73 14.37 16.59 20.43 23.46 28.74
1
0.78 0.80 0.81 0.75 0.77 0.78
2
0.85 0.85
0.92 0.86 0.81 0.83
3
0.93 0.92
4
5
0.86 0.78 0.76 0.76 0.75
0.95 0.89 0.89 0.83
1.14 0.97 0.98 0.88 0.86 0.83
0.97
(a) Does nozzle type affect shape measurement? First use Minitab to create Boxplots to compare the nozzles and then
use analysis of variance to make conclusion.
To create Boxplot use the data named as Example 13.47.csv that is included with the hw. From Minitab open this
data in a new worksheet. Select from the menu Graph->Boxplot->With Categorical Variables. Select the response
variable, and the categorical variables (factors)
To perform ANOVA, select Stat->ANOVA->General Linear Model->FitGeneral Linear Model.
(b) Use Fisher’s LSD method (manually) to determine specific differences among the nozzles 4 and 5, and 2 and 3.
Do mean shape measurements differ between these groups?
Now, use Minitab to determine which group means differ significantly at alpha=0.05? Use Minitab to create
Fisher Individual 95 %confidence Intervals.
(c) Analyze the residuals from this experiment.< Back
NozzleType Velocity Shape
11.73 0.78
1
2
11.73
0.85
3
11.73
0.93
4
11.73
1.14
5
11.73
0.97
1
14.37
0.8
2
14.37
0.85
3
14.37
0.92
4
14.37
0.97
5
14.37
0.86
1
16.59
0.81
2
16.59
0.92
3
16.59
0.95
4
16.59 0.98
5
16.59 0.78
1
20.43
0.75
2
20.43
0.86
3
20.43
0.89
4
20.43
0.88
5
20.43 0.76
1
23.46
0.77
2
23.46
0.81
3
23.46 0.89
4
23.46
0.86
5
23.46
0.76
1
28.74
0.78
2
28.74 0.83
3
28.74
0.83
4
28.74
0.83
5
28.74 0.75
Example_13.47.csvBack
Example_13.13.csv
AirVoid Strength
Low
Low
106
00
90
Low
103
Low
00
90
Low
79
Low
88
Low
92
Low
95
Medium 80
Medium 69
Medium 94
Medium 91
Medium 70
Medium 83
Medium 87
Medium
83
High
78
High
80
High
62
High
69
High
76
High
85
High
69
High
85
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