An article in Wear (1992, Vol. 152, pp. 171-181) presents data on the fretting wear of mild steel and oil viscosity. Representative data follow withx- oil viscosity and y - wear volume (10“ cubic millimeters). y 240 181 193 155 172 110 113 75 94 x 1.6 9.4 15.5 20.0 22.0 35.5 43.0 40.5 33.0 Round your answers to two decimal places (e.g. 98.76). (a) Construct a scatter plot of the data. Does a simple linear regression model appear to be plausible? O Yes O No (b) Fit the simple linear regression model using least squares. Find an estimate of o. Bo+ B iX Bo = %3D (c) Predict fretting wear when viscosity x - 30.
An article in Wear (1992, Vol. 152, pp. 171-181) presents data on the fretting wear of mild steel and oil viscosity. Representative data follow withx- oil viscosity and y - wear volume (10“ cubic millimeters). y 240 181 193 155 172 110 113 75 94 x 1.6 9.4 15.5 20.0 22.0 35.5 43.0 40.5 33.0 Round your answers to two decimal places (e.g. 98.76). (a) Construct a scatter plot of the data. Does a simple linear regression model appear to be plausible? O Yes O No (b) Fit the simple linear regression model using least squares. Find an estimate of o. Bo+ B iX Bo = %3D (c) Predict fretting wear when viscosity x - 30.
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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Transcribed Image Text:An article in Wear (1992, Vol. 152, pp. 171-181) presents data on the fretting wear of mild steel and oil viscosity. Representative data
follow withx- oil viscosity and y - wear volume (10“ cubic millimeters).
y 240 181 193 155 172 110 113 75
94
x 1.6
9.4
15.5 20.0 22.0 35.5 43.0 40.5 33.0
Round your answers to two decimal places (e.g. 98.76).
(a) Construct a scatter plot of the data. Does a simple linear regression model appear to be plausible?
O Yes
O No
(b) Fit the simple linear regression model using least squares. Find an estimate of o.
F = Bo+ B 1x
Bo =
i
i
(c) Predict fretting wear when viscosity x- 30.
(d) Obtain the fitted value of y when x- 22.0 and calculate the corresponding residual.
e =
i
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