MSTL-002 Assignment Solution 2021

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MSTL-002 Solved Assignment 2021 

Assignment Paper

MSTL-002 Solved Assignment 2021

Subject Name

Industrial Statistics Lab

No.of Pages in Solution

69

Course

PGDAST

Language

ENGLISH

Session

2021

Last Date for Submission of Assignment

For June Examination 30th April 2021 or as per dates given in the website

For December Examination 31st October 2021 or as per dates given in the website

 

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MSTL-002 Assignment Sample Solution

MSTL-002 Assignment Question Paper 

MSTL-002: Industrial Statistics Lab                          Download Question Paper 

Note: 

  1. All questions are compulsory.
  2. Solve the following questions in MS Excel 2007.
  3. Take the screenshots of the final output/spreadsheet.
  4. Paste all screenshots in the assignment booklet with all necessary hypotheses, interpretation, etc.

Q 1      The marketing manager of a transportation network company offering taxi services in a metro city wanted to study the waiting times of customers to get a taxi during the peak hours. A subgroup of 15 customers was selected (one at each ten minutes interval during the hour) and the time in minutes was measured from the point each customer booked the taxi to when he or she began the trip. The results of 40 days period were as under.

Sample No.

1

2

3

4

5

6

7

8

Obs. 1

8.7

6.6

6.7

5.6

6.9

8.2

7.3

5.7

Obs. 2

6.4

6.3

7.5

8.7

7.1

6.7

8.8

8.1

Obs. 3

8.8

7.3

9.5

7.1

10

7.2

7.1

5.2

Obs. 4

6.1

6.7

8.1

9.1

7.5

7.1

8.7

8.5

Obs. 5

8.6

8.5

9.3

6.9

9.8

7.1

8.9

7

Obs. 6

5.6

5.5

7.5

7.9

6.3

6.9

8

7.3

Obs. 7

8

7.9

8.7

6.3

9.2

6.5

8.3

4.4

Obs. 8

5.3

5.9

7.3

8.3

6.7

8

7.9

7.7

Obs. 9

5.8

5.8

7.7

8.1

6.5

7.7

8.2

7.5

Obs. 10

8.2

8.1

8.9

6.5

9.4

6.7

8.5

6.3

Obs. 11

5.5

6.1

7.5

8.5

6.9

6.5

8.1

7.9

Obs. 12

8.1

7.9

8.8

6.3

9.2

8.6

8.3

6.4

Obs. 13

6.5

6.4

8.7

9.1

7.3

6.8

8.9

8.4

Obs. 14

9.3

9.2

10.1

7.3

10.7

7.5

8.9

5

Obs. 15

6.1

6.8

8.4

9.6

7.7

7.3

9.2

8.9

 

Sample No.

9

10

11

12

13

14

15

16

Obs. 1

9.3

9

9

5.8

7.1

6

8.5

6.7

Obs. 2

8.5

8.2

7.2

7.9

7.7

7.3

10.7

8

Obs. 3

7.5

5.4

7.2

8.5

9.1

8

6.4

6.5

Obs. 4

8.7

8.6

7.7

8.3

8.5

7.7

11.1

8.4

Obs. 5

8.1

7.3

7

8.3

7.5

7.9

6.2

6.3

Obs. 6

7.8

7.4

6.5

7.1

8.6

6.5

9.9

7.2

Obs. 7

8.4

6.7

6.4

7.7

7.8

7.2

5.6

5.7

Obs. 8

7.3

7.8

6.9

7.5

8.1

6.9

10.3

7.6

Obs. 9

8.1

7.6

6.7

7.3

8.8

6.7

10.1

7.4

Obs. 10

8.6

4.8

6.6

8

8

7.5

5.8

5.9

Obs. 11

8.2

8

7.1

7.8

8.3

7.1

10.5

7.8

Obs. 12

7.5

4.6

6.4

7.8

8.8

7.3

5.6

5.8

Obs. 13

9.1

8.6

7.5

8.2

10

7.5

11.5

8.3

Obs. 14

9.7

7.7

7.4

9

9

8.4

6.5

6.6

Obs. 15

8.4

9.1

7.9

8.7

7.8

8

11.9

8.8

 

Sample No.

17

18

19

20

21

22

23

24

Obs. 1

8.6

6.3

6.6

5.5

6.8

8.1

7.2

5.6

Obs. 2

5.6

6.9

8.5

8.6

7

6.6

8.7

8

Obs. 3

8.7

8.6

7.5

7

9.9

7.1

9

5.1

Obs. 4

6

5.2

8.6

9

7.4

7

7.9

8.4

Obs. 5

8.5

8.4

6.8

6.8

9.7

7

8.8

6.9

Obs. 6

6.6

5.4

7.6

7.8

6.2

8

7.9

7.2

Obs. 7

7.9

7.8

8.6

6.2

9.1

6.4

8.2

4.3

Obs. 8

5.2

5.8

7.8

8.2

6.6

6.2

7.1

7.6

Obs. 9

5

6.4

7.8

8

6.4

6

8.1

7.4

Obs. 10

8.1

8

8.8

6.4

9.3

6.6

8.4

4.5

Obs. 11

5.4

4.6

8

8.4

6.8

6.4

7.4

7.8

Obs. 12

8

7.8

8.7

6.2

9.1

6.4

8.2

6.3

Obs. 13

7.6

6.3

8.8

9

7.1

6.7

9.1

8.3

Obs. 14

9.2

9

10

7.1

10.5

7.3

9.5

8.3

Obs. 15

6

6.7

9

9.5

7.6

7.2

8.3

8.8

 

Sample No.

25

26

27

28

29

30

31

32

Obs. 1

7.5

9.2

8.9

5.7

7

8.5

8.4

6.6

Obs. 2

8.1

8.1

7.1

7.8

9.3

7.2

10.6

7.9

Obs. 3

9.1

6.7

7.1

8.4

7.4

7.9

5.2

6.4

Obs. 4

7.9

8.5

7.6

8.2

8.1

7.6

11.7

8.3

Obs. 5

8.9

5.9

6.9

8.2

8.4

7.8

6.1

6.2

Obs. 6

7.3

7.3

6.4

7

8.5

6.4

9.8

7.1

Obs. 7

8.3

5.9

6.3

7.6

8.7

7.1

4.4

5.6

Obs. 8

7.2

7.7

6.8

7.4

7.3

6.8

10.9

7.5

Obs. 9

7.5

7.5

6.6

7.2

8.7

6.6

10

7.3

Obs. 10

8.5

6.2

6.5

7.9

8.9

7.4

4.6

5.8

Obs. 11

7.4

7.9

7

7.7

7.5

7

11.1

7.7

Obs. 12

8.3

5.3

6.3

7.7

7.9

7.2

5.5

5.7

Obs. 13

8.4

8.5

7.3

8.1

9.9

7.4

11.3

8.2

Obs. 14

9.6

6.9

7.2

8.8

8.9

8.3

5

6.5

Obs. 15

8.3

8.9

7.8

8.6

8.4

7.9

12.6

8.7

 

Sample No.

33

34

35

36

37

38

39

40

Obs. 1

8.5

5.2

6.5

9.7

6.2

7.6

6.5

9.1

Obs. 2

8.1

5.7

7.4

7.8

8.5

8.3

7.8

11.5

Obs. 3

8.6

8.5

9.3

7.7

9.1

6.8

8.6

6.8

Obs. 4

5.9

6.6

7.1

8.2

8.9

9.1

8.3

11.9

Obs. 5

8.4

8.3

9.1

7.5

9

8

8.4

6.6

Obs. 6

7.3

4.9

7.3

6.9

7.6

6.2

7

10.6

Obs. 7

7.8

7.7

8.5

6.8

8.3

8.3

7.8

6

Obs. 8

5.1

5.8

6.4

7.4

8.1

8.7

7.4

11.1

Obs. 9

7.5

5.2

9.8

7.1

7.9

8.8

7.2

10.8

Obs. 10

8

7.9

8.7

7.1

8.5

8.6

8

6.2

Obs. 11

5.3

6.1

6.6

7.6

8.3

8.9

7.6

11.3

Obs. 12

7.9

7.7

8.6

6.9

8.3

9.3

7.8

6

Obs. 13

8.4

8

8.4

6.6

7.4

9.2

10.4

8.4

Obs. 14

9.1

8.9

9.9

7.3

7.2

9.7

10.2

8.1

Obs. 15

5.9

6.7

7.3

10.4

10.2

7.3

8.2

11.9

The manager of this company needs to construct the suitable control charts for variability as well as average to infer whether the waiting times of customers for getting a taxi is under control or not. If it is out-of-control, also construct the revised control charts.

Q 2      A publisher recorded the total number of pages in 25 published books and also the number of typing errors that have been made in preparing the final print of the books.

The results are given in the following table:

Day

Number of pages

Errors

1

180

5

2

187

11

3

205

11

4

180

25

5

180

11

6

172

5

7

183

11

8

194

16

9

187

14

10

180

4

11

198

16

12

216

8

13

198

16

14

198

14

15

187

5

16

172

11

17

180

8

18

201

16

19

187

5

20

190

11

21

180

8

22

198

6

23

180

14

24

180

8

25

169

11

26

150

7

27

156

14

28

150

14

29

150

17

30

144

14

31

162

7

32

156

14

33

150

16

34

180

18

35

156

4

36

144

21

37

150

9

38

164

15

39

156

16

40

150

5

The publisher needs to set up a suitable control chart for the number of errors to check whether the number of errors in a state of control or not. Also computes the revised

             control limits, if necessary.                                                                                                

Q 3  A researcher is interested to check the relationship between the salaries of workers involved in the production process of a company. To accomplish this, she/he has decided to develop a multiple regression model to predict their weekly salaries. For this purpose, he/she has selected a random sample of 50 workers involved in the production process. The information on their current monthly salaries in hundreds (Y), lengths of employment in months (X1), and job classifications (X2; 0 for technical job and 1 for clerical job) are summarised in the following table:

Employee

Y

X1

X2

1

495

74

1

2

406

51

0

3

567

130

1

4

523

25

1

5

575

178

1

6

437

42

0

7

664

242

1

8

491

57

1

9

472

72

0

10

407

129

1

11

378

17

1

12

725

318

1

13

600

296

0

14

440

39

0

15

662

280

1

16

523

116

1

17

428

19

1

18

535

94

1

19

533

193

0

20

528

49

1

21

446

26

0

22

528

40

1

23

498

51

1

24

478

48

1

25

507

32

0

26

478

24

1

27

645

234

1

28

577

281

0

29

554

335

1

30

654

336

1

31

566

77

1

32

433

90

0

33

466

89

1

34

365

30

0

35

677

225

0

36

473

36

1

37

644

305

1

38

685

316

1

39

356

11

0

40

444

23

1

41

478

94

0

42

408

81

0

43

456

58

0

44

409

22

0

45

691

359

0

46

463

69

0

47

436

93

0

48

413

16

1

49

734

412

0

50

463

69

0

 

  1. i) Prepare a scatter plot to get an idea about the relationship among the variables. ii) Fit a linear regression model and its related analysis at 1% level of significance. iii) Does the fitted regression model satisfy the linearity and normality assumptions? 
  2. iv)Also, draw both fitted regression lines on the scatter plot.              

 

Q 4      The marketing manager of a transportation network company offering taxi services in a metro city wishes to improve customer service and taxi scheduling based on the daily levels of customers in the past 10 weeks. The numbers of customers during that period are given below:

Week

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

1

334

499

262

232

435

351

223

2

170

249

203

268

329

168

293

3

110

179

240

114

266

99

90

4

155

234

81

253

314

93

278

5

95

164

225

99

264

107

283

6

270

183

308

125

194

255

129

7

223

132

239

268

143

323

332

8

212

369

390

369

218

495

320

9

479

540

414

590

390

460

663

10

549

739

734

684

642

866

832

  1. Determine the seasonal indices for the given data using a 7-day moving averages.
  2. Obtain the deseasonalised values.
  • Fit the appropriate trend for the deseasonalised data using the least-squares method by matrix approach that best describes the data.
  1. Project the number of customers on Wednesday of the 52th
  2. Plot the original data, the de-seasonalised data, and the trend values.

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MSTL-002 Solved Assignment 2021

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