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Is there a linear correlation between x and y? Use α = 0.01.   a.) Yes, because the correlation coefficient is not in the critical region. b.) Yes, because the correlation coefficient is in the critical region. c.) No, because the correlation coefficient is in the critical region. d.) No, because the correlation coefficient is not in the critical region.   C. What is correlation coefficient when the point (2,9) is excluded?   r=_________ (Round to three decimal places as needed.)   Is there a linear correlation between x and y? Use

Is there a linear correlation between x and y? Use α = 0.01.   a.) Yes, because the correlation coefficient is not in the critical region. b.) Yes, because the correlation coefficient is in the critical region. c.) No, because the correlation coefficient is in the critical region. d.) No, because the correlation coefficient is not in the critical region.   C. What is correlation coefficient when the point (2,9) is excluded?   r=_________ (Round to three decimal places as needed.)   Is there a linear correlation between x and y? Use

MATLAB: An Introduction with Applications
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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Is there a linear correlation between x and y? Use α = 0.01.

 

a.) Yes, because the correlation coefficient is not in the critical region.

b.) Yes, because the correlation coefficient is in the critical region.

c.) No, because the correlation coefficient is in the critical region.

d.) No, because the correlation coefficient is not in the critical region.

 

C. What is correlation coefficient when the point (2,9) is excluded?

 

r=_________ (Round to three decimal places as needed.)

 

Is there a linear correlation between x and y? Use α= 0.01

 

a.) No, because the correlation coefficient is in the critical region.

b.) Yes, because the correlation coefficient is not in the critical region.

c.) Yes, because the correlation coefficient is in the critical region.

d.) No, because the correlation coefficient is not in the critical region.

 

Refer to the accompanying scatterplot. a. Examine the pattern of all 10 points and subjectively determine whether there appears to be a strong correlation between x and y. b. Find the value of the correlation coefficient r and determine whether there is a linear correlation. c. Remove the point with coordinates (2,9) and find the correlation coefficient r and determine whether there is a linear correlation. d. What do you conclude about the possible effect from a single pair of values? Click here to view a table of critical values for the correlation coefficient. --- a. Do the data points appear to have a strong linear correlation? - Yes (checked) - No b. What is the value of the correlation coefficient for all 10 data points? r = ___ (Simplify your answer. Round to three decimal places as needed.) --- **Graph Explanation:** The scatterplot is positioned in the upper right corner and depicts 10 data points. The majority of points form a tight cluster at the lower right corner, with one outlier located further up. This pattern suggests that the data may not follow a perfect linear trend.
Transcribed Image Text:Refer to the accompanying scatterplot. a. Examine the pattern of all 10 points and subjectively determine whether there appears to be a strong correlation between x and y. b. Find the value of the correlation coefficient r and determine whether there is a linear correlation. c. Remove the point with coordinates (2,9) and find the correlation coefficient r and determine whether there is a linear correlation. d. What do you conclude about the possible effect from a single pair of values? Click here to view a table of critical values for the correlation coefficient. --- a. Do the data points appear to have a strong linear correlation? - Yes (checked) - No b. What is the value of the correlation coefficient for all 10 data points? r = ___ (Simplify your answer. Round to three decimal places as needed.) --- **Graph Explanation:** The scatterplot is positioned in the upper right corner and depicts 10 data points. The majority of points form a tight cluster at the lower right corner, with one outlier located further up. This pattern suggests that the data may not follow a perfect linear trend.
### Critical Values of r for Testing Correlation This table provides critical values of the Pearson correlation coefficient \( r \) for testing the null hypothesis \( H_0: \rho = 0 \) (no correlation) against the alternative hypothesis \( H_1: \rho \neq 0 \), using a two-tailed test. | \( n \) | \(\alpha = .05\) | \(\alpha = .01\) | |---------|----------------|-----------------| | 4 | .950 | .990 | | 5 | .878 | .959 | | 6 | .811 | .917 | | 7 | .754 | .875 | | 8 | .707 | .834 | | 9 | .666 | .798 | | 10 | .632 | .765 | | 11 | .602 | .735 | | 12 | .576 | .708 | | 13 | .553 | .684 | | 14 | .532 | .661 | | 15 | .514 | .641 | | 16 | .497 | .623 | | 17 | .482 | .606 | | 18 | .468 | .590 | | 19 | .456 | .575 | | 20 | .444 | .561 | | 25 | .396 | .505 | | 30 | .361 | .463 | | 35 | .335 | .430 | | 40 | .312 | .402 | | 45 | .294 | .378 | | 50 | .279 | .361 | | 60 | .254 | .330 | | 70 | .232 | .304 | | 80 | .220 | .286 | | 90 | .207 | .269 | | 100 | .196 | .256 | **Note:** To test \( H_0: \rho = 0 \) against \( H_1: \rho \neq 0 \), reject \( H_
Transcribed Image Text:### Critical Values of r for Testing Correlation This table provides critical values of the Pearson correlation coefficient \( r \) for testing the null hypothesis \( H_0: \rho = 0 \) (no correlation) against the alternative hypothesis \( H_1: \rho \neq 0 \), using a two-tailed test. | \( n \) | \(\alpha = .05\) | \(\alpha = .01\) | |---------|----------------|-----------------| | 4 | .950 | .990 | | 5 | .878 | .959 | | 6 | .811 | .917 | | 7 | .754 | .875 | | 8 | .707 | .834 | | 9 | .666 | .798 | | 10 | .632 | .765 | | 11 | .602 | .735 | | 12 | .576 | .708 | | 13 | .553 | .684 | | 14 | .532 | .661 | | 15 | .514 | .641 | | 16 | .497 | .623 | | 17 | .482 | .606 | | 18 | .468 | .590 | | 19 | .456 | .575 | | 20 | .444 | .561 | | 25 | .396 | .505 | | 30 | .361 | .463 | | 35 | .335 | .430 | | 40 | .312 | .402 | | 45 | .294 | .378 | | 50 | .279 | .361 | | 60 | .254 | .330 | | 70 | .232 | .304 | | 80 | .220 | .286 | | 90 | .207 | .269 | | 100 | .196 | .256 | **Note:** To test \( H_0: \rho = 0 \) against \( H_1: \rho \neq 0 \), reject \( H_
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