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 (10,1) 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. LOADING... 010010xy A scatterplot has a horizontal x-scale from 0 to 10 in increments of 1 and vertical y-scale from 0 to 10 in increments of 1. Ten points are plotted with nine points (1, 10), (2, 10), (3, 10), (1, 9), (2, 9), (3, 9), (1, 8), (2, 8), and (3, 8) forming a square and the tenth point (10, 1) below and to the right of it. a. Do the data points appear to have a strong linear correlation? Yes No b. What is the value of the correlation coefficient for all 10 data points? r=enter your response here (Simplify your answer. Round to three decimal places as needed.) Is there a linear correlation between x and y? Use α = 0.05. A. No, because the correlation coefficient is in the critical region. B. Yes, because the correlation coefficient is in the critical region. C. No, because the correlation coefficient is not in the critical region. D. Yes, because the correlation coefficient is not in the critical region. c. What is the correlation coefficient when the point (10,1) is excluded? r=enter your response here (Round to three decimal places as needed.) Is there a linear correlation between x and y? Use α = 0.05. A. No, because the correlation coefficient is in the critical region. B. Yes, because the correlation coefficient is not in the critical region. C. No, because the correlation coefficient is not in the critical region. D. Yes, because the correlation coefficient is in the critical region. d. What do you conclude about the possible effect from a single pair of values? A single pair of values does not change the conclusion. The effect from a single pair of values can change the conclusion.
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 (10,1) 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. LOADING... 010010xy A scatterplot has a horizontal x-scale from 0 to 10 in increments of 1 and vertical y-scale from 0 to 10 in increments of 1. Ten points are plotted with nine points (1, 10), (2, 10), (3, 10), (1, 9), (2, 9), (3, 9), (1, 8), (2, 8), and (3, 8) forming a square and the tenth point (10, 1) below and to the right of it. a. Do the data points appear to have a strong linear correlation? Yes No b. What is the value of the correlation coefficient for all 10 data points? r=enter your response here (Simplify your answer. Round to three decimal places as needed.) Is there a linear correlation between x and y? Use α = 0.05. A. No, because the correlation coefficient is in the critical region. B. Yes, because the correlation coefficient is in the critical region. C. No, because the correlation coefficient is not in the critical region. D. Yes, because the correlation coefficient is not in the critical region. c. What is the correlation coefficient when the point (10,1) is excluded? r=enter your response here (Round to three decimal places as needed.) Is there a linear correlation between x and y? Use α = 0.05. A. No, because the correlation coefficient is in the critical region. B. Yes, because the correlation coefficient is not in the critical region. C. No, because the correlation coefficient is not in the critical region. D. Yes, because the correlation coefficient is in the critical region. d. What do you conclude about the possible effect from a single pair of values? A single pair of values does not change the conclusion. The effect from a single pair of values can change the conclusion.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Refer to the accompanying
10
points and subjectively determine whether there appears to be a strong (10,1)
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.
LOADING...
|
|
a. Do the data points appear to have a strong linear correlation?
Yes
No
b. What is the value of the correlation coefficient for all
10
data points?r=enter your response here
(Simplify your answer. Round to three decimal places as needed.)Is there a linear correlation between x and y? Use
α
=
0.05.
No,
because the correlation coefficient is
in
the critical region.Yes,
because the correlation coefficient is
in
the critical region.No,
because the correlation coefficient is
not in
the critical region.Yes,
because the correlation coefficient is
not in
the critical region.c. What is the correlation coefficient when the point
(10,1)
is excluded?r=enter your response here
(Round to three decimal places as needed.)Is there a linear correlation between x and y? Use
α
=
0.05.
No,
because the correlation coefficient is
in
the critical region.Yes,
because the correlation coefficient is
not in
the critical region.No,
because the correlation coefficient is
not in
the critical region.Yes,
because the correlation coefficient is
in
the critical region.d. What do you conclude about the possible effect from a single pair of values?
A single pair of values does not change the conclusion.
The effect from a single pair of values can change the conclusion.
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