/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q22BSC Testing for a Linear Correlation... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

Testing for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of A = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.)

22. Crickets and Temperature A classic application of correlation involves the association between the temperature and the number of times a cricket chirps in a minute. Listed below are the numbers of chirps in 1 min and the corresponding temperatures in °F (based on data from The Song of Insects, by George W. Pierce, Harvard University Press). Is there sufficient evidence to conclude that there is a linear correlation between the number of chirps in 1 min and the temperature?

Actress

28

30

29

61

32

33

45

29

62

22

44

54

Actor

43

37

38

45

50

48

60

50

39

55

44

33

Short Answer

Expert verified

The scatterplot is shown below:

The value of the correlation coefficient is 0.874.

The p-value is 0.005.

There is enough evidence to support the claim for a linear correlation between chirps in one minute and temperature.

Step by step solution

01

Given information

The data is recorded forchirps of crickets and temperatures in degrees Fahrenheit.

Chirps in 1 min

Temperature

882

69.7

1188

93.3

1104

84.3

864

76.3

1200

88.6

1032

82.6

960

71.6

900

79.6

02

Sketch a scatterplot

Scatterplot projects a paired set of observationsontwo axes scaled for the two variables.

Steps to sketch a scatterplot:

  1. Describe two axes, x and y, for chirps in 1 minute and temperature, respectively.
  2. Mark the points on the graph.

The graph is shown below.

03

Compute the measure of the correlation coefficient

The correlation coefficient formula is

\(r = \frac{{n\sum {xy} - \left( {\sum x } \right)\left( {\sum y } \right)}}{{\sqrt {n\left( {\sum {{x^2}} } \right) - {{\left( {\sum x } \right)}^2}} \sqrt {n\left( {\sum {{y^2}} } \right) - {{\left( {\sum y } \right)}^2}} }}\).

Describe variables x and y as chirps in 1 minute and temperature, respectively.

The valuesare listed in the table below:

x

y

\({x^2}\)

\({y^2}\)

\(xy\)

882

69.7

777924

4858.09

61475.4

1188

93.3

1411344

8704.89

110840.4

1104

84.3

1218816

7106.49

93067.2

864

76.3

746496

5821.69

65923.2

1200

88.6

1440000

7849.96

106320

1032

82.6

1065024

6822.76

85243.2

960

71.6

921600

5126.56

68736

900

79.6

810000

6336.16

71640

\(\sum x = 8130\)

\(\sum y = 646\)

\(\sum {{x^2}} = 8391204\)

\(\sum {{y^2} = } \;52626.6\)

\(\sum {xy\; = \;} 663245.4\)

Substitute the values in the formula:

\(\begin{aligned} r &= \frac{{8\left( {663245.4} \right) - \left( {8130} \right)\left( {646} \right)}}{{\sqrt {8\left( {8391204} \right) - {{\left( {8130} \right)}^2}} \sqrt {8\left( {52626.6} \right) - {{\left( {646} \right)}^2}} }}\\ &= 0.874\end{aligned}\)

Thus, the correlation coefficient is 0.874.

04

Step 4:Conduct a hypothesis test for correlation

Definethe actual measure of the correlation coefficient between chirps and temperature as\(\rho \).

For testing the claim, form the hypotheses:

\(\begin{array}{l}{H_o}:\rho = 0\\{H_a}:\rho \ne 0\end{array}\)

The samplesize is 8(n).

The test statistic is computed as follows:

\(\begin{aligned} t &= \frac{r}{{\sqrt {\frac{{1 - {r^2}}}{{n - 2}}} }}\\ &= \frac{{0.874}}{{\sqrt {\frac{{1 - {{\left( {0.874} \right)}^2}}}{{8 - 2}}} }}\\ &= 4.406\end{aligned}\)

Thus, the test statistic is 4.406.

The degree of freedom is

\(\begin{aligned} df &= n - 2\\ &= 8 - 2\\ &= 6.\end{aligned}\)

The p-value is computed from the t-distribution table.

\(\begin{aligned} p{\rm{ - value}} &= 2P\left( {t > 4.406} \right)\\ &= 0.0045\\ &\approx 0.005\end{aligned}\)

Thus, the p-value is 0.005.

Since thep-value is lesser than 0.05, the null hypothesis is rejected.

Therefore, there is enough evidence to conclude a linear correlation between chirps in 1 minute and temperature.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Critical Thinking: Is the pain medicine Duragesic effective in reducing pain? Listed below are measures of pain intensity before and after using the drug Duragesic (fentanyl) (based on data from Janssen Pharmaceutical Products, L.P.). The data are listed in order by row, and corresponding measures are from the same subject before and after treatment. For example, the first subject had a measure of 1.2 before treatment and a measure of 0.4 after treatment. Each pair of measurements is from one subject, and the intensity of pain was measured using the standard visual analog score. A higher score corresponds to higher pain intensity.

Pain Intensity Before Duragesic Treatment

1.2

1.3

1.5

1.6

8

3.4

3.5

2.8

2.6

2.2

3

7.1

2.3

2.1

3.4

6.4

5

4.2

2.8

3.9

5.2

6.9

6.9

5

5.5

6

5.5

8.6

9.4

10

7.6










Pain Intensity After Duragesic Treatment

0.4

1.4

1.8

2.9

6

1.4

0.7

3.9

0.9

1.8

0.9

9.3

8

6.8

2.3

0.4

0.7

1.2

4.5

2

1.6

2

2

6.8

6.6

4.1

4.6

2.9

5.4

4.8

4.1










Matched Pairs The methods of Section 9-3 can be used to test a claim about matched data. Identify the specific claim that the treatment is effective, then use the methods of Section 9-3 to test that claim.

Stocks and Sunspots. Listed below are annual high values of the Dow Jones Industrial Average (DJIA) and annual mean sunspot numbers for eight recent years. Use the data for Exercises 1–5. A sunspot number is a measure of sunspots or groups of sunspots on the surface of the sun. The DJIA is a commonly used index that is a weighted mean calculated from different stock values.

DJIA

14,198

13,338

10,606

11,625

12,929

13,589

16,577

18,054

Sunspot

Number

7.5

2.9

3.1

16.5

55.7

57.6

64.7

79.3

Hypothesis Test The mean sunspot number for the past three centuries is 49.7. Use a 0.05 significance level to test the claim that the eight listed sunspot numbers are from a population with a mean equal to 49.7.

Exercises 13–28 use the same data sets as Exercises 13–28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493.

Use the CPI/subway fare data from the preceding exercise and find

the best predicted subway fare for a time when the CPI reaches 500. What is wrong with this prediction?

Interpreting a Graph The accompanying graph plots the numbers of points scored in each Super Bowl to the last Super Bowl at the time of this writing. The graph of the quadratic equation that best fits the data is also shown in red. What feature of the graph justifies the value of\({R^2}\)= 0.255 for the quadratic model?

let the predictor variable x be the first variable given. Use the given data to find the regression equation and the best predicted value of the response variable. Be sure to follow the prediction procedure summarized in Figure 10-5 on page 493. Use a 0.05 significance level.

For 30 recent Academy Award ceremonies, ages of Best Supporting Actors (x) and ages of Best Supporting Actresses (y) are recorded. The 30 paired ages yield\(\bar x = 52.1\)years,\(\bar y = 37.3\)years, r= 0.076, P-value = 0.691, and

\(\hat y = 34.4 + 0.0547x\). Find the best predicted value of\(\hat y\)(age of Best Supporting Actress) in 1982, when the age of the Best Supporting Actor (x) was 46 years.

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.