Statistical Quality Control (ISS (Statistical Services) Statistics Paper IV): Questions 6 - 8 of 34

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Question number: 6

» Statistical Quality Control » Control Charts » Attributes

Essay Question▾

Describe in Detail

The following are the figures of defectives in 22 lots each containing 2,000 bulbs. Obtain the 3-σ control limits for the p chart.

Given are observations find control limits for the P - Chart

Given are observations find control limits for P Chart

425

430

216

341

225

322

280

306

337

305

356

402

216

264

126

409

193

326

280

389

451

420

Explanation

we have n = 2000

Given are observations Correct control limits for P Chart

Given are observations control limits for P Chart

S. No.

d

1

425

0.2125

2

430

0.215

3

216

0.108

4

341

0.1705

5

225

0.1125

6

322

0.161

7

280

0.14

8

306

0.153

9

337

0.1685

10

305

0.1525

… (45 more words) …

Question number: 7

» Statistical Quality Control » Control Charts » Variable

Essay Question▾

Describe in Detail

A electric Company uses a process to paint cars with a coat of enamel. During each shift, a sample of five cars is selected and the thickness of the paint in mm is determined. On the basis of and R charts, Check whether the production is under control?

Check whether production is under control

Find if production is under control

Sample No.

Observations

1

2.6

2.3

2.6

2.7

2.7

2

2.6

2.6

2.4

2.8

2.3

3

2.4

2.3

2.4

2.5

2.3

4

2.7

2.4

2.3

2.6

2.8

5

2.6

2.6

2.5

2.8

2.1

6

2.2

2.2

2.7

2.3

2.6

7

2.0

2.6

2.4

2.2

2.3

8

2.5

2.6

2.6

2.7

2.8

9

2.4

2.4

2.2

2.8

2.3

10

2.6

2.3

2.0

2.5

2.4

11

3.1

3.0

3.5

2.8

3.0

12

2.4

2.8

2.2

2.9

2.5

13

2.1

3.2

2.5

2.6

2.8

14

2.2

2.8

2.1

2.2

2.4

15

2.4

3.0

2.5

2.5

2.0

16

3.1

2.6

2.6

2.8

2.1

17

2.9

2.4

2.9

1.3

1.8

18

1.9

1.6

2.6

3.3

3.3

19

2.3

2.6

2.7

2.8

3.2

20

2.0

2.8

2.3

1.8

2.9

Explanation

Check whether production is under control Total, mean and range

Find if production is under control

Sample No.

Observations

Total

Sample Mean ()

Sample Range (R)

1

2.6

2.3

2.6

2.7

2.7

12.70

2.54

0.40

2

2.6

2.6

2.4

2.8

2.3

12.70

2.54

0.50

3

2.4

2.3

2.4

2.5

2.3

11.90

2.38

0.20

4

2.7

2.4

2.3

2.6

2.8

12.80

2.56

0.50

5

2.6

2.6

2.5

2.8

2.1

12.60

2.52

0.70

6

2.2

2.2

2.7

2.3

2.6

12.00

2.40

0.50

7

2.0

2.6

2.4

2.2

2.3

11.50

2.30

0.60

8

2.5

2.6

2.6

2.7

2.8

13.20

2.64

0.30

9

2.4

2.4

2.2

2.8

2.3

12.10

2.42

0.60

10

2.6

2.3

2.0

2.5

2.4

11.80

2.36

0.60

11

3.1

3.0

3.5

2.8

3.0

15.40

3.08

0.70

12

2.4

2.8

2.2

2.9

2.5

12.80

2.56

0.70

13

2.1

3.2

2.5

2.6

2.8

13.20

2.64

1.10

14

2.2

2.8

2.1

2.2

2.4

11.70

2.34

0.70

15

2.4

3.0

2.5

2.5

2.0

12.40

2.48

1.00

16

3.1

2.6

2.6

2.8

2.1

13.20

2.64

1.00

17

2.9

2.4

2.9

1.3

1.8

11.30

2.26

1.60

18

1.9

1.6

2.6

3.3

3.3

12.70

2.54

1.70

19

2.3

2.6

2.7

2.8

3.2

13.60

2.72

0.90

20

2.0

2.8

2.3

1.8

2.9

11.80

2.36

1.10

Total

50.28

15.40

… (121 more words) …

Question number: 8

» Statistical Quality Control » Acceptance Sampling by Attributes

Essay Question▾

Describe in Detail

What is Type –I Error? What is type-II error? What is probability of rejecting a lot which contains acceptable quality level known as?

Explanation

Type I error— rejecting a lot that is good.

When the null hypothesis is true and we reject it, it is known as type I error.

Producer’s risk is the probability of rejecting a good lot considering it as a bad lot by the consumer. Hence, Producer’s Risk is also known as Type I error.

Knowing type I and II errors

Knowing Type I and II Errors

Identifying type I and II errors in sampling

… (114 more words) …

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