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Control Charts for p. In Exercises 5–12, use the given process data to construct a control chart for p. In each case, use the three out-of-control criteria listed near the beginning of this section and determine whether the process is within statistical control. If it is not, identify which of the three out-of-control criteria apply

Voting Rate In each of recent and consecutive years of presidential elections, 1000 people of voting age in the United States were randomly selected and the number who voted was determined, with the results listed below. Comment on the voting behavior of the population.

631 619 608 552 536 526 531 501 551 491 513 553 568

Short Answer

Expert verified

The following p chart is constructed for the given proportion of voters:

The following features are observed from the chart:

  • At least eight points lie below the central line.
  • Points lie beyond UCL and LCL.

As a result, the process is not statistically controlled.

Furthermore, the actual voter turnout in the United States has increased in recent years, and actual statistics do not match those presented in the problem.

Step by step solution

01

Given information

Data are given on the number of voters in 13 randomly selected samples of the people of voting age.

The size of each sample is 1000.

02

Important values of p chart

Let\(\bar p\)be the estimated proportion of voters in all the samples.

It is computed as follows:

\(\begin{array}{c}\bar p = \frac{{{\rm{Total}}\;{\rm{number}}\;{\rm{of}}\;{\rm{defectives}}\;{\rm{from}}\;{\rm{all}}\;{\rm{samples}}\;{\rm{combined}}}}{{{\rm{Total}}\;{\rm{number}}\;{\rm{of}}\;{\rm{observations}}}}\\ = \frac{{631 + 618 + 608 + ..... + 568}}{{13\left( {1000} \right)}}\\ = \frac{{7180}}{{13000}}\\ = 0.5523\end{array}\)

The value of\(\bar q\)is computed as shown:

\(\begin{array}{c}\bar q = 1 - 0.5523\\ = 0.4477\end{array}\)

The value of the lower control limit (LCL) is computed below:

\(\begin{array}{c}LCL = \bar p - 3\sqrt {\frac{{\bar p\bar q}}{n}} \\ = 0.5523 - 3\sqrt {\frac{{\left( {0.5523} \right)\left( {0.4477} \right)}}{{1000}}} \\ = 0.5051\end{array}\)

The value of the upper control limit (UCL) is computed below:

\(\begin{array}{c}UCL = \bar p + 3\sqrt {\frac{{\bar p\bar q}}{n}} \\ = 0.5523 + 3\sqrt {\frac{{\left( {0.5523} \right)\left( {0.4477} \right)}}{{1000}}} \\ = 0.5995\end{array}\)

03

Computation of the fraction of voters

The sample fraction of voters for the ith region can be computed as shown below:

\({p_i} = \frac{{{d_i}}}{{1000}}\)

Here,

\({p_i}\)isthe sample fraction of voters for the ith region, and

\({d_i}\)isthe number of voters in the ith region.

The computation of fraction of voters for the ith region is given as follows:

S.No.

Defectives (d)

Sample fraction of voters (p)

1

631

0.631

2

619

0.619

3

608

0.608

4

552

0.552

5

536

0.536

6

526

0.526

7

531

0.531

8

501

0.501

9

551

0.551

10

491

0.491

11

513

0.513

12

553

0.553

13

568

0.568

04

Construction of the p chart

Follow the given steps to construct the p chart:

  • Mark the values 1, 2, ...,13on the horizontal axis and label it “Sample.”
  • Mark the values 0.50, 0.52, 0.54, ……, 0.64 on the vertical axis and label it “Proportion.”
  • Plot a straight line corresponding to the value 0.5523 on the vertical axis and label it (on the left side) “\(\bar P\;or\;\bar p = 0.5523\).”
  • Plot a horizontal line corresponding to the value 0.5051 on the vertical axis and label it “LCL=0.5051.”
  • Similarly, plot a horizontal line corresponding to the value 0.5995 on the vertical axis and label it “UCL=0.5995.”
  • Mark all13 sample points (number of defectives of the ith region) on the graph and join the dots using straight lines.

The following p chart is obtained:

05

Analysis of the p chart

The following featuresare observed from the chart:

  • There are at least eight points that lie below the central line.
  • There is at least one point that lies beyond the upper control limit (UCL).
  • There is at least one point that lies below the lower control limit (LCL).

Thus, the criteria indicate that the process is not within statistical control.

Moreover, the actual voter turnout in the US has increased in recent years.The actual values are not close to those given in the problem.

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Most popular questions from this chapter

Sunspots and the DJIA Use the data from Exercise 5 and find the equation of the regression line. Then find the best predicted value of the DJIA in the year 2004, when the sunspot number was 61. How does the result compare to the actual DJIA value of 10,855?

What is the difference between an R chart and an\(\bar x\) chart?

Energy Consumption. Exercises 1–5 refer to the amounts of energy consumed in the author’s home. (Most of the data are real, but some are fabricated.) Each value represents energy consumed (kWh) in a two-month period. Let each subgroup consist of the six amounts within the same year. Data are available for download atwww.TriolaStats.com.


Jan.-Feb.

Mar.-April

May-June

July-Aug.

Sept.-Oct.

Nov.-dec.

Year 1

3637

2888

2359

3704

3432

2446

Year 2

4463

2482

2762

2288

2423

2483

Year 3

3375

2661

2073

2579

2858

2296

Year 4

2812

2433

2266

3128

3286

2749

Year 5

3427

578

3792

3348

2937

2774

Year 6

4016

3458

3395

4249

4003

3118

Year 7

4016

3458

3395

4249

4003

3118

Year 8

4016

3458

3395

4249

4003

3118

Energy Consumption: R Chart Let each subgroup consist of the 6 values within a year. Construct an R chart and determine whether the process variation is within statistical control. If it is not, identify which of the three out-of-control criteria lead to rejection of statistically stable variation

Control Charts for p. In Exercises 5–12, use the given process data to construct a control chart for p. In each case, use the three out-of-control criteria listed near the beginning of this section and determine whether the process is within statistical control. If it is not, identify which of the three out-of-control criteria apply

Euro Coins Consider a process of minting coins with a value of one euro. Listed below are the numbers of defective coins in successive batches of 10,000 coins randomly selected on consecutive days of production.

32 21 25 19 35 34 27 30 26 33

Quarters. In Exercises 9–12, refer to the accompanying table of weights (grams) of quarters minted by the U.S. government. This table is available for download at www.TriolaStats.com.

Day

Hour 1

Hour 2

Hour 3

Hour 4

Hour 5

\(\bar x\)

s

Range

1

5.543

5.698

5.605

5.653

5.668

5.6334

0.0607

0.155

2

5.585

5.692

5.771

5.718

5.72

5.6972

0.0689

0.186

3

5.752

5.636

5.66

5.68

5.565

5.6586

0.0679

0.187

4

5.697

5.613

5.575

5.615

5.646

5.6292

0.0455

0.122

5

5.63

5.77

5.713

5.649

5.65

5.6824

0.0581

0.14

6

5.807

5.647

5.756

5.677

5.761

5.7296

0.0657

0.16

7

5.686

5.691

5.715

5.748

5.688

5.7056

0.0264

0.062

8

5.681

5.699

5.767

5.736

5.752

5.727

0.0361

0.086

9

5.552

5.659

5.77

5.594

5.607

5.6364

0.0839

0.218

10

5.818

5.655

5.66

5.662

5.7

5.699

0.0689

0.163

11

5.693

5.692

5.625

5.75

5.757

5.7034

0.0535

0.132

12

5.637

5.628

5.646

5.667

5.603

5.6362

0.0235

0.064

13

5.634

5.778

5.638

5.689

5.702

5.6882

0.0586

0.144

14

5.664

5.655

5.727

5.637

5.667

5.67

0.0339

0.09

15

5.664

5.695

5.677

5.689

5.757

5.6964

0.0359

0.093

16

5.707

5.89

5.598

5.724

5.635

5.7108

0.1127

0.292

17

5.697

5.593

5.78

5.745

5.47

5.657

0.126

0.31

18

6.002

5.898

5.669

5.957

5.583

5.8218

0.185

0.419

19

6.017

5.613

5.596

5.534

5.795

5.711

0.1968

0.483

20

5.671

6.223

5.621

5.783

5.787

5.817

0.238

0.602

Quarters: \(\bar x\)-Chart Treat the 5 measurements from each day as a sample and construct an \(\bar x\)- chart. What does the result suggest?

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