MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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a) For these data, R? = 0.28. What is the correlation? Round to 2 decimal places.
0.53
How can you tell if it is positive or negative?
OWe know the correlation is negative due to the negative association shown in the scatterplot
O We know the correlation is positive due to the negative association shown in the scatterplot
O We know the correlation is negative due to the positive association shown in the scatterplot
O We know the correlation is positive due to the positive association shown in the scatterplot
b) Examine the residual plot. What do you observe? Is a simple least squares fit appropriate for these data?
O The residuals appear to be fan shaped, indicating non-constant variance, so a simple least squares fit
is not appropriate for these data.
O The residuals appear to be fan shaped, indicating constant variance, so a simple least squares fit is
not appropriate for these data.
O The residuals appear to be fan shaped, indicating non-constant variance, so a simple least squares fit
is appropriate for these data.
O The residuals appear to be fan shaped, indicating constant variance, so a simple least squares fit is
appropriate for these data.
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Transcribed Image Text:a) For these data, R? = 0.28. What is the correlation? Round to 2 decimal places. 0.53 How can you tell if it is positive or negative? OWe know the correlation is negative due to the negative association shown in the scatterplot O We know the correlation is positive due to the negative association shown in the scatterplot O We know the correlation is negative due to the positive association shown in the scatterplot O We know the correlation is positive due to the positive association shown in the scatterplot b) Examine the residual plot. What do you observe? Is a simple least squares fit appropriate for these data? O The residuals appear to be fan shaped, indicating non-constant variance, so a simple least squares fit is not appropriate for these data. O The residuals appear to be fan shaped, indicating constant variance, so a simple least squares fit is not appropriate for these data. O The residuals appear to be fan shaped, indicating non-constant variance, so a simple least squares fit is appropriate for these data. O The residuals appear to be fan shaped, indicating constant variance, so a simple least squares fit is appropriate for these data.
Exercise 7.33 gives a scatterplot displaying the relationship between the percent
of families that own their home and the percent of the population living in urban
areas. Below is a similar scatterplot, excluding District of Columbia, as well as
the residuals plot. There were 51 cases.
40
60
80
% Urban population
% Who own home
-10
55
65
75
09
OL
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Transcribed Image Text:Exercise 7.33 gives a scatterplot displaying the relationship between the percent of families that own their home and the percent of the population living in urban areas. Below is a similar scatterplot, excluding District of Columbia, as well as the residuals plot. There were 51 cases. 40 60 80 % Urban population % Who own home -10 55 65 75 09 OL
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