TOPIC: Linear Regression

College Algebra
1st Edition
ISBN:9781938168383
Author:Jay Abramson
Publisher:Jay Abramson
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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TOPIC: Linear Regression

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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 with x = 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 .
(c) Predict fretting wear when viscosity x= 30.
(d) Obtain the fitted value of y whenx= 22.0 and calculate the corresponding residual.
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 with x = 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 . (c) Predict fretting wear when viscosity x= 30. (d) Obtain the fitted value of y whenx= 22.0 and calculate the corresponding residual.
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