3. The following data were collected in an experiment to study the relationship between excursion (in KPa) and wear (in mg). I 150 175 200 225 250 275 y 10.4 12.4 14.9 15.0 13.9 11.9 (a) Plot the data. What is the name of the plot? (b) Verify that the best prediction equation is given by: y = -32.445714 + 0.431543r-0.000983². The calculator steps are: STAT-CALC-5 QuadReg L1,L2, say, ENTER. (c) Graph the residual plot.

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
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4 of 9
3
3. The following data were collected in an experiment to study the relationship
between excursion (in KPa) and wear (in mg).
2150 175 200 225 250 275
y 10.4 12.4 14.9 15.0 13.9 11.9
(a) Plot the data. What is the name of the plot?
(b) Verify that the best prediction equation is given by: = -32.445714 +
0.431543r-0.0009832. The calculator steps are: STAT CALC 5 QuadReg
L1,L2, say, ENTER.
(e) Graph the residual plot.
(d) What percent of the total variation is explained by the variation in a?
(e) Graph the fit on the same plot in part (a).
(f) Is this a good fit to the data. Briefly and clearly explain yourself.
Transcribed Image Text:4 of 9 3 3. The following data were collected in an experiment to study the relationship between excursion (in KPa) and wear (in mg). 2150 175 200 225 250 275 y 10.4 12.4 14.9 15.0 13.9 11.9 (a) Plot the data. What is the name of the plot? (b) Verify that the best prediction equation is given by: = -32.445714 + 0.431543r-0.0009832. The calculator steps are: STAT CALC 5 QuadReg L1,L2, say, ENTER. (e) Graph the residual plot. (d) What percent of the total variation is explained by the variation in a? (e) Graph the fit on the same plot in part (a). (f) Is this a good fit to the data. Briefly and clearly explain yourself.
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