13b. The answer in the back of the book states it is 8.88-.147t I don\'t know ho
ID: 3306036 • Letter: 1
Question
13b. The answer in the back of the book states it is 8.88-.147t I don't know how that answer was calculated. hapter 2 Forecasting 93 A quality control analyst has kept a record of the defective rate of a process he has been trying to improve during a period of about four weeks. The following data (percent- ages) were recorded: 13. Week 10.2 9.4 8.4 7.8 8.2 7.3 7.0 6.5 Monday Tuesday Wednesday 72 .6.8 6.3 5.0 Thursday Friday 6.8 6.0 5.4 48 94 9.0 8.2 7.1 Determine daily relatives for the defective rate. b. a. Compute a linear trend equation for the defective rate. Use your answers from the preceding two parts to predict the defective rate fo each day of Week 5. c. A TV repair shop located near a large hospital provides rental TVs to hospital patients.Ac- cording to shop invoices, the number of TVs rented out per day for the last 12 days were Day 14. Rentals Day RentalsExplanation / Answer
Answer:
Data entered as follows.
Do regression analysis time t as x variable and defective rate as y variable.
t
defective rate
1
10.2
2
8.2
3
7.2
4
6.8
5
9.4
6
9.4
7
7.3
8
6.8
9
6
10
9
11
8.4
12
7
13
6.3
14
5.4
15
8.2
16
7.8
17
6.5
18
5
19
4.8
20
7.1
Result.
Regression Analysis
r²
0.339
n
20
r
-0.583
k
1
Std. Error
1.246
Dep. Var.
defective rate
ANOVA table
Source
SS
df
MS
F
p-value
Regression
14.3538
1
14.3538
9.25
.0070
Residual
27.9342
18
1.5519
Total
42.2880
19
Regression output
confidence interval
variables
coefficients
std. error
t (df=18)
p-value
95% lower
95% upper
Intercept
8.8826
0.5787
15.350
8.76E-12
7.6668
10.0984
t
-0.1469
0.0483
-3.041
.0070
-0.2484
-0.0454
The regression line is
defective rate = 8.8826 – 0.1469*t
t
defective rate
1
10.2
2
8.2
3
7.2
4
6.8
5
9.4
6
9.4
7
7.3
8
6.8
9
6
10
9
11
8.4
12
7
13
6.3
14
5.4
15
8.2
16
7.8
17
6.5
18
5
19
4.8
20
7.1
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