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Use the survey results given in Exercise 1 and use a 0.05 significance level to test the claim that the majority of adults learn about medical symptoms more often from the internet than from their doctor.

Short Answer

Expert verified

There is enough evidence at 0.05 level of significance to support the claim that the majority of adults learn about medical symptoms more often from the internet than from their doctor.

Step by step solution

01

Given information

The sample number of adults is\(n = 2015\).

Number of adults who said that they learn about medical symptoms more often from the internet than from their doctor is 1108 adults who. The level of confidence is 95%.

02

State the null and alternate hypotheses

Let p be the true representative of the population proportionof adults who learn about medical symptoms more often from the internet than from their doctor.

The researcher claimsthat the majority of adults learn about medical symptoms more often from the internet than from their doctor.So, the statistical hypotheses are formed as shown:

\(\begin{aligned}{l}{H_0}:p = 0.50\\{H_1}:p > 0.50\end{aligned}\)

03

Calculate the level of significance and critical value

As the level of confidence is 95%, the level of significance is 0.05.

From the Z-table, the right-tailed critical value at 0.05 level of significance is 1.645.

04

Calculate the sample proportion

The sample proportion of adults who said that they learn about medical symptoms more often from the internet than from their doctor is

\(\begin{aligned}{c}\hat p = \frac{{1108}}{{2015}}\\ = 0.549876.\end{aligned}\)

Therefore, the sample proportion is \(0.549876\).

05

Calculate the test statistic

The test statistic is computed below:

\(\begin{aligned}{c}Z = \frac{{\hat p - p}}{{\sqrt {\frac{{p\left( {1 - p} \right)}}{n}} }}\\ = \frac{{0.549876 - 0.50}}{{\sqrt {\frac{{0.50\left( {1 - 0.50} \right)}}{{2015}}} }}\\ = 4.4777\end{aligned}\)

Thus, the value of the test statistic is 4.48.

06

State the decision

Since the calculated value (4.4889) of the test statistic is greater than the critical value (1.645), the null hypothesis is rejected.

07

Provide the conclusion

There is enough evidence at 0.05 level of significance to support the claim that the majority of adults learn about medical symptoms more often from the internet than from their doctor.

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Most popular questions from this chapter

In Exercises 5โ€“8, use the following two control charts that result from testing batches of newly manufactured aircraft altimeters, with 100 in each batch. The original sample values are errors (in feet) obtained when the altimeters are tested in a pressure chamber that simulates an altitude of 6000 ft. The Federal Aviation Administration requires an error of no more than 40 ft at that altitude.

What is the value of\(\bar R\)? In general, how is a value of\(\bar R\)obtained?

In Exercises 5โ€“8, use the following two control charts that result from testing batches of newly manufactured aircraft altimeters, with 100 in each batch. The original sample values are errors (in feet) obtained when the altimeters are tested in a pressure chamber that simulates an altitude of 6000 ft. The Federal Aviation Administration requires an error of no more than 40 ft at that altitude.

What is the value of\(\bar \bar x\)? In general, how is a value of\(\bar \bar x\)found?

Minting Quarters Specifications for a quarter require that it be 8.33% nickel and 91.67% copper; it must weigh 5.670 g and have a diameter of 24.26 mm and a thickness of 1.75 mm; and it must have 119 reeds on the edge. A quarter is considered to be defective if it deviates substantially from those specifications. A production process is monitored, defects are recorded and the accompanying control chart is obtained. Does this process appear to be within statistical control? If not, identify any out-of-control criteria that are satisfied. Is the manufacturing process deteriorating?

Quarters. In Exercises 9โ€“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: Run Chart Treat the 100 consecutive measurements from the 20 days as individual values and construct a run chart. What does the result suggest?

Energy Consumption. Exercises 1โ€“5 refer to the amounts of energy consumed in the authorโ€™s home. (Most of the data are real, but some are fabricated.) Each value represents the 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 at www.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: Run Chart Construct a run chart for the 48 values. Does there appear to be a pattern suggesting that the process is not within statistical control?

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