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A manufacturing company wants to develop a budget to predict how monthly mainten

ID: 3061779 • Letter: A

Question

A manufacturing company wants to develop a budget to predict how monthly maintenance costs vary with activity levels. Management is trying to decide whether hours used or units produced is the better measure of maintenance cost. Monthly data for the preceding 24 months is given below.

Month

Hours

Units

Maintenance

Month

Hours

Units

Maintenance

1

1304

111

30800

13

1301

138

30500

2

1397

114

32900

14

1438

123

34000

3

1465

133

33800

15

1194

124

29000

4

1232

129

29900

16

1355

144

32600

5

1487

147

34200

17

1149

120

28200

6

1223

130

28700

18

1244

120

30000

7

1238

122

29600

19

1158

106

28800

8

1406

119

31600

20

1418

150

33100

9

1179

105

28000

21

1117

121

26700

10

1272

125

30300

22

1340

116

31200

11

1344

126

31600

23

1334

129

30900

12

1324

145

31800

24

1387

150

32700

Use regression to determine which measure, Hours or Units (or both), should be used for the budget.

Your boss asks you to predict the maintenance cost when 1587 Hours are used and 178 Units are produced. Comment on how you would a respond to this prediction request from your boss.

Month

Hours

Units

Maintenance

Month

Hours

Units

Maintenance

1

1304

111

30800

13

1301

138

30500

2

1397

114

32900

14

1438

123

34000

3

1465

133

33800

15

1194

124

29000

4

1232

129

29900

16

1355

144

32600

5

1487

147

34200

17

1149

120

28200

6

1223

130

28700

18

1244

120

30000

7

1238

122

29600

19

1158

106

28800

8

1406

119

31600

20

1418

150

33100

9

1179

105

28000

21

1117

121

26700

10

1272

125

30300

22

1340

116

31200

11

1344

126

31600

23

1334

129

30900

12

1324

145

31800

24

1387

150

32700

Explanation / Answer

Below is given output of R software.

we first run linear regression in R.

Model and summary given below.

> model<-lm(maintaince~hours+unit)

> model

Call:

lm(formula = maintaince ~ hours + unit)

Model is given by

Coefficients:

(Intercept) hours unit  

5740.964 18.420 8.685  

> summary(model)

Call:

lm(formula = maintaince ~ hours + unit)

Residuals:

Min 1Q Median 3Q Max

-1072.87 -265.81 25.83 313.19 808.17

Coefficients:

Estimate Std. Error t value Pr(>|t|)   

(Intercept) 5740.964 1334.495 4.302 0.000316 ***

hours 18.420 1.136 16.219 2.36e-13 ***

unit 8.685 9.047 0.960 0.347985   

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 489.5 on 21 degrees of freedom

Multiple R-squared: 0.9476, Adjusted R-squared: 0.9426

F-statistic: 189.7 on 2 and 21 DF, p-value: 3.6e-14

Q.1) determine which measure, Hours or Units (or both), should be used for the budget.

I.e. we want to use t test to check significance of variables.

a) for hour

we want to test

Ho:- hour is not significant

V/s

H1:- hour is significant

Here we get direct P value in Coefficient column for unit.

P value = 2.36e-13 < 0.05 (at 95% Level of significance)

Therefore we reject Ho.

Conclusion:- hour is singnificant.

b) for unit

we want to test

Ho:- Unit is not significant

V/s

H1:- Unit is significant

Here we get direct P value in Coefficient column for unit.

P value =  0.347985 > 0.05(at 95% Level of significance)

Therefore we accept Ho.

Conclusion:- Unit is not singnificant.

from a) & b)

Hours should be used for the budget.

Q.2) boss asks you to predict the maintenance cost when 1587 Hours are used and 178 Units are produced.

So we fitted linear regression model above, we use that model to predict the value of  maintenance cost .

Our linear regression model is given by,

maintainance= 5740.964+(18.420*hours) + (8.685* unit)

Hours= 1587 , units = 178

Using values in above model.

maintainance =  5740.964 + (18.420*1587) + (8.685* 178)

maintainnance = 36519.43

predicted value of the maintenance cost when 1587 Hours are used and 178 Units are produced is 36519.43

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