Statistical Quality Control Archives - Basic Statistics and Data Analysis

1. Variation in the items produced in a factory may be due to

Chance factors

Assignable causes

Both (a) and (b)

None of the above

2. For a normal population probability of any point falling outside the 3-$\sigma$ control line is

0.5

0.05

0.02

0.0027

3. The chart which is applicable when the quality of product is a discrete variable

Xbar-chart

P-chart

R-chart

C-chart

4. Statistical quality control methods are extensively used in the industrial production process because of

Reduction in cost

Greater efficiency

Timely detection of faults

All of the above

5. Variation due to assignable causes in the product occurs due to:

Faulty process

Carelessness of operators

Poor quality of raw materials

All of the above

6. The chart that are used to deal with the characteristics which are not possible to measure, but can observe as absent or present from the product

Xbar-chart

P-chart

R-chart

C-chart

7. The control limits for P-chart is

$ UCL_{\overline{P}}=\overline{P}-3\sqrt{\overline{P}(1-\overline{P})/n} $ and $LCL_{\overline{P}} =\overline{P}-3\sqrt{\overline{P}(1-\overline{P})/n} $

$ UCL_{\overline{P}}=\overline{P}+3\sqrt{\overline{P}(1-\overline{P})/n} $ and $LCL_{\overline{P}} =\overline{P}-3\sqrt{\overline{P}(1-\overline{P})/n} $

$ UCL_{\overline{P}}=\overline{P}+3\sqrt{\overline{P}(1-\overline{P})} $ and $LCL_{\overline{P}} =\overline{P}-3\sqrt{\overline{P}(1-\overline{P})/n} $

$ UCL_{\overline{P}}=\overline{P}+3\sqrt{\overline{P}(1-\overline{P})/n} $ and $LCL_{\overline{P}} =\overline{P}-3\sqrt{\overline{P}(1-\overline{P})} $

8. Control charts consists of

Three control lines

Upper and lower control limits

The level of the process

All of the above

9. To control the quality of a specific resistance of a wire, one can use

Xbar-chart

R-chart

Both (a) and (b)

None of these

10. The faults due to assignable causes:

Can be removed

Cannot be removed

Can sometimes be removed

All of the above

11. Control charts in statistical quality control are meant for

Describing the pattern of variation

Checking whether the variability in the product is within the tolerance limits or not

Uncovering whether the variability in the product due to assignable causes or not

All of the above

12. The control limits for $\overline{X}$-chart is

$ LCL_{\overline{X}} = \mu -3\frac{\sigma}{\sqrt{n}}$ and $UCL_{\overline{X}} = \mu +3\frac{\sigma}{\sqrt{n}} $

$ LCL_{\overline{X}} = \mu +3\frac{\sigma}{\sqrt{n}}$ and $UCL_{\overline{X}} = \mu -3\frac{\sigma}{\sqrt{n}} $

$ LCL_{\overline{X}} = \mu +3\frac{\sigma}{\sqrt{n}}$ and $UCL_{\overline{X}} = \mu +3\frac{\sigma}{\sqrt{n}} $

$ LCL_{\overline{X}} = \mu -3\frac{\sigma}{\sqrt{n}}$ and $UCL_{\overline{X}} = \mu -3\frac{\sigma}{\sqrt{n}} $

13. The control limits for C-chart is

$ UCL=\hat{\lambda}+4\sqrt{\hat{\lambda}} $ and $ LCL = \hat{\lambda} – 4 \sqrt{\hat{\lambda}} $

$ UCL=\hat{\lambda}+3\sqrt{\hat{\lambda}} $ and $ LCL = \hat{\lambda} – 3 \sqrt{\hat{\lambda}} $

$ UCL=\hat{\lambda}+2\sqrt{\hat{\lambda}} $ and $ LCL = \hat{\lambda} – 2 \sqrt{\hat{\lambda}} $

$ UCL=\hat{\lambda}+\frac{1}{2}\sqrt{\hat{\lambda}} $ and $ LCL = \hat{\lambda} -\frac{1}{2} \sqrt{\hat{\lambda}} $

14. The control limits for R-chart is

$ LCL_R = (1-3C)\overline{R} $ and $ UCL_R =(1+3C)\overline{R} $

$ LCL_R = (3-C)\overline{R} $ and $ UCL_R =(1+3C)\overline{R} $

$ LCL_R = (1-3C)\overline{R} $ and $ UCL_R =(3+C)\overline{R} $

$ LCL_R = (3-C)\overline{R} $ and $ UCL_R =(3+C)\overline{R} $

15. Chance or random variation in the manufactured product is:

Controllable

Not controllable

Both (a) and (b)

None of the above

Category: Statistical Quality Control

MCQs Quality Control 1

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