Question
QUESTION 5 All firms struggle with the question of how to limit the number of defective items produced. One firm believes that the number of
QUESTION 5
All firms struggle with the question of how to limit the number of defective items produced. One firm believes that the number of defectives depends upon three factors - the variation in temperature at the time of production, the rate at which items are being produced, and which shift produces the items (the morning shift believes the afternoon shift are less experienced and the afternoon shift believes the morning shift is less capable).
The quality control officer collected data over thirty (30) shifts on four variables:
- 1. The number of defective items (per 1000 produced)
- 2. The variation in the temperature during the shift
- 3. The rate at which items were produced during the shift (number per hour)
- 4. Whether or not the shift was the AM or PM shift (AM = 1, PM = 0)
The resulting regression output is provided in the table below:
Summary Output
Regression Statistics
Multiple R
0.948
R Squared
0.899
Adjusted R Squared
0.883
Standard Error
6.644
Observations
30
ANOVA
df
SS
MS
F
P - value
Regression
3
9825.76
3275.25
77.16
0.0001
Residual
26
1103.54
42.44
Total
29
10929.29
Coefficient
Std. Errors
t
P - value (Two Tail)
Intercept
-28.756
60.147
-0.448
0.658
Temperature
26.242
9.051
2.899
0.008
Rate
0.0508
0.126
0.403
0.682
AM/PM
-1.746
0.803
-2.176
0.039
- (a) State clearly the model which is to be tested as well as the estimated equation. Interpret all values.
(5 marks)
(b) Conduct all of the necessary hypothesis tests to determine the usefulness of the model and variables. Write brief report in NON TECHNICAL language summarising the results of these tests and what it means for maintaining quality.
(11 marks)
(c) To what extent does the model not explain the variation in the production of defectives. What statistic did you use to answer this question?
(2 marks)
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