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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. (a) What type of relation appears to exist between time between eruptions and length of eruption? OA. Linear, negative association B. Linear, positive association OC. A nonlinear pattern. OD. No association. (b) Does the residual plot confirm that the relation between time between eruptions and length of e A. Yes. The plot of the residuals shows no discernible pattern, so a linear model is appropriate OB. No. The plot of the residuals shows that the spread of the residuals is increasing or decreas OC. Yes. The plot of the residuals shows a discernible pattern, implying that the explanatory and OD. No. The plot of the residuals shows no discernible pattern, implying that the explanatory and (c) The coefficient of determination is found to be 94.8%. 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.) 0.10- 0.08- 0.06 0.04 0.02 0.00- -0.02- -0.04- -0.06- -0.08- -0.10+ 11 Time, x 12.15 11.58 11.4 12.05 12.13 11.29 Residual plot of eruption data. Residuals vs. Time Print 11.8 12.2 12.6 Time Length, y 1.86 1.68 1.82 1.88 1.62 Done - X Q Q 2.00- 1.90- 1.80- 1.70- Time, x 11.69 12.28 Scatter plot of eruption data. 1.60- 11.58 11.75 1.50+ Time between Eruptions vs. Length of Eruption . 11 11.4 11.8 Time Print : Length, y 1.70 12.2 1.92 1.74 1.73 12.6 Done O OU - Q D X

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. (a) What type of relation appears to exist between time between eruptions and length of eruption? OA. Linear, negative association B. Linear, positive association OC. A nonlinear pattern. OD. No association. (b) Does the residual plot confirm that the relation between time between eruptions and length of e A. Yes. The plot of the residuals shows no discernible pattern, so a linear model is appropriate OB. No. The plot of the residuals shows that the spread of the residuals is increasing or decreas OC. Yes. The plot of the residuals shows a discernible pattern, implying that the explanatory and OD. No. The plot of the residuals shows no discernible pattern, implying that the explanatory and (c) The coefficient of determination is found to be 94.8%. 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.) 0.10- 0.08- 0.06 0.04 0.02 0.00- -0.02- -0.04- -0.06- -0.08- -0.10+ 11 Time, x 12.15 11.58 11.4 12.05 12.13 11.29 Residual plot of eruption data. Residuals vs. Time Print 11.8 12.2 12.6 Time Length, y 1.86 1.68 1.82 1.88 1.62 Done - X Q Q 2.00- 1.90- 1.80- 1.70- Time, x 11.69 12.28 Scatter plot of eruption data. 1.60- 11.58 11.75 1.50+ Time between Eruptions vs. Length of Eruption . 11 11.4 11.8 Time Print : Length, y 1.70 12.2 1.92 1.74 1.73 12.6 Done O OU - Q D X

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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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. (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 e A. Yes. The plot of the residuals shows no discernible pattern, so a linear model is appropriate B. No. The plot of the residuals shows that the spread of the residuals is increasing or decreas C. Yes. The plot of the residuals shows a discernible pattern, implying that the explanatory and D. No. The plot of the residuals shows no discernible pattern, implying that the explanatory and (c) The coefficient of determination is found to be 94.8%. 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.) Residual Residual plot of eruption data. 0.10+ 0.08- 0.06- 0.04- 0.02- 0.00- -0.02- -0.04- -0.06- -0.08- -0.10+ 11 Time, x 12.15 11.58 12.05 12.13 11.29 Residuals vs. Time 11.4 Print ● 11.8 Time ● ● ● 12.2 12.6 Done Length, y 1.86 1.68 1.82 1.88 1.62 Q X Length Scatter plot of eruption data. 2.00- 1.90- 1.80- 1.70- 1.60- Time, x 11.69 12.28 11.58 11.75 1.50- 11 Time between Eruptions vs. Length of Eruption 11.4 11.8 Time Print Length, y 1.70 1.92 1.74 1.73 12.2 12.6 Done Q X
Transcribed Image Text: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. (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 e A. Yes. The plot of the residuals shows no discernible pattern, so a linear model is appropriate B. No. The plot of the residuals shows that the spread of the residuals is increasing or decreas C. Yes. The plot of the residuals shows a discernible pattern, implying that the explanatory and D. No. The plot of the residuals shows no discernible pattern, implying that the explanatory and (c) The coefficient of determination is found to be 94.8%. 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.) Residual Residual plot of eruption data. 0.10+ 0.08- 0.06- 0.04- 0.02- 0.00- -0.02- -0.04- -0.06- -0.08- -0.10+ 11 Time, x 12.15 11.58 12.05 12.13 11.29 Residuals vs. Time 11.4 Print ● 11.8 Time ● ● ● 12.2 12.6 Done Length, y 1.86 1.68 1.82 1.88 1.62 Q X Length Scatter plot of eruption data. 2.00- 1.90- 1.80- 1.70- 1.60- Time, x 11.69 12.28 11.58 11.75 1.50- 11 Time between Eruptions vs. Length of Eruption 11.4 11.8 Time Print Length, y 1.70 1.92 1.74 1.73 12.2 12.6 Done Q X
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