(a) (1) Use least-squares regression to fit a straight line to the following data: x 1 2 3 4 5 6 7 8 9 10 y 1.3 3.5 4.2 5.0 7.0 8.8 10.1 12.5 13.0 15.6 Along with the slope and intercept, compute the standard error of the estimate and the correlation coefficient. Plot the data and the regression line.

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Author:Amos Gilat
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Chapter1: Starting With Matlab
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(a) (1) Use least-squares regression to fit a straight
line to the following data:
x 1 23 4 5 6 7 8 9 10
y 1.3 3.5 4.2 5.0 7.0 8.8 10.1 12.5 13.0 15.6
Along with the slope and intercept, compute the
standard error of the estimate and the correlation
coefficient. Plot the data and the regression line.
(2) Repeat the analysis but for a straight line with a
zero intercept.
(3) Calculate the difference of R-values of these two
regression models.
Transcribed Image Text:(a) (1) Use least-squares regression to fit a straight line to the following data: x 1 23 4 5 6 7 8 9 10 y 1.3 3.5 4.2 5.0 7.0 8.8 10.1 12.5 13.0 15.6 Along with the slope and intercept, compute the standard error of the estimate and the correlation coefficient. Plot the data and the regression line. (2) Repeat the analysis but for a straight line with a zero intercept. (3) Calculate the difference of R-values of these two regression models.
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