(c) The coefficient of determination is found to be 88.1%. Provide an interpretation of this value. The least squares regression line explains% of the variation in (Type an integer or a decimal. Do not round.)

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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Length, y
Length, y
The following data represent the time between eruptions and the length of eruption for 8 randomly selected geyser
eruptions. Complete parts (a) through (c) below.
Click here to view a scatter plot of the data.
Click here to view a residual plot of the data.
Time, x
Time, x
12.19
1.87
11.67
1.70
11.56
1.67
12.29
1.88
11.95
1.79
11.64
1.73
12.17
1.92
11.69
1.71
11.34
1.69
(a) What type of relation appears to exist between time between eruptions and length of eruption?
A. Linear, negative association
B. Linear, positive association
C. A nonlinear pattern.
D. No association.
(b) Does the residual plot confirm that the relation between time between eruptions and length of eruption is linear?
A. Yes. The plot of the residuals shows a discernible pattern, implying that the explanatory and response variables are linearly related.
B. No. The plot of the residuals shows no discernible pattern, implying that the explanatory and response variables are not linearly related.
C. No. The plot of the residuals shows that the spread of the residuals is increasing or decreasing, violating the requirements of a linear model.
D. Yes. The plot of the residuals shows no discernible pattern, so a linear model is appropriate.
(c) The coefficient of determination is found to be 88.1%. Provide an interpretation of this value.
The least squares regression line explains % of the variation in
(Type an integer or a decimal. Do not round.)
Transcribed Image Text:Length, y Length, y The following data represent the time between eruptions and the length of eruption for 8 randomly selected geyser eruptions. Complete parts (a) through (c) below. Click here to view a scatter plot of the data. Click here to view a residual plot of the data. Time, x Time, x 12.19 1.87 11.67 1.70 11.56 1.67 12.29 1.88 11.95 1.79 11.64 1.73 12.17 1.92 11.69 1.71 11.34 1.69 (a) What type of relation appears to exist between time between eruptions and length of eruption? A. Linear, negative association B. Linear, positive association C. A nonlinear pattern. D. No association. (b) Does the residual plot confirm that the relation between time between eruptions and length of eruption is linear? A. Yes. The plot of the residuals shows a discernible pattern, implying that the explanatory and response variables are linearly related. B. No. The plot of the residuals shows no discernible pattern, implying that the explanatory and response variables are not linearly related. C. No. The plot of the residuals shows that the spread of the residuals is increasing or decreasing, violating the requirements of a linear model. D. Yes. The plot of the residuals shows no discernible pattern, so a linear model is appropriate. (c) The coefficient of determination is found to be 88.1%. Provide an interpretation of this value. The least squares regression line explains % of the variation in (Type an integer or a decimal. Do not round.)
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