Use the given data set to complete parts (a) through (c) below. (Use a= 0.05.)1081311144127.466.7712.737.127.818.846.085.388.156.425.74yClick here to view a table of critical values for the correlation coefficient.4'8' 12 1612 1612 16*48 12 16b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables.The linear correlation coefficient is r=.(Round to three decimal places as needed.) Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below.O A. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables.O B. There is sufficient evidence to support the claim of a linear correlation between the two variables.O C. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables.O D. There is insufficient evidence to support the claim of a linear correlation between the two variables.c. Identify the feature of the data that would be missed if part (b) was completed without constructing the scatterplot. Choose the correct answer below.O A. The scatterplot reveals a perfect straight-line pattern and does not contain any outliers.O B. The scatterplot does not reveal a perfect straight-line pattern, and contains one outlier.O C. The scatterplot reveals a perfect straight-line pattern, except for the presence of one outlier.O D. The scatterplot does not reveal a perfect straight-line pattern.

==================================================== x y xy x2 y2 10 7.46 74.6 100 55.6516…

Use the given data set to complete parts (a) through (c) below. (Use a= 0.05.) 10 7.46 13 12.73 11 7.81 14 8.84 12 8.15 4 6.77 7.12 6.08 5.38 6.42 5.74 9 Click here to view a table of critical values for the correlation coefficient. O 12 16 12 16 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r=N (Round to three decimal places as needed.)

Use the given data set to complete parts (a) through (c) below. (Use a= 0.05.) 10 7.46 13 12.73 11 7.81 14 8.84 12 8.15 4 6.77 7.12 6.08 5.38 6.42 5.74 9 Click here to view a table of critical values for the correlation coefficient. O 12 16 12 16 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r=N (Round to three decimal places as needed.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Use the given data set to complete parts (a) through (c) below. (Use a = 0.05.) 10 8 13 11 14 4 12 7 y 9.14 8.13 8.73 8.77 9.25 8.11 6.13 3.11 9.13 7.27 4.74 Click here to view a table of critical values for the correlation coefficient. a. Construct a scatterplot. Choose the correct graph below. A. В. C. D. Ay 10- 10- 10- 10- 8- 8- 8- 8- 6- 6- 6- ... 4- 4- 4- 4- 2- 2- 2- 2- 04 4 0- 0- 0- 4 12 16 8 12 16 4 8 8 12 16 b. Find the linear correlation coefficient, r, then detemine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r=. (Round to three decimal places as needed.) Using the linear correlation coefficient found in the previous step, detemine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below. A. There is insufficient evidence to support the claim of a nonlinear correlation between the two…
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Use the given data set to complete parts (a). (Use α=0.05.) a. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r= (Round to three decimal places as needed.)
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