An article in the Journal of the American Statistical Association ['Markov Chain Monte Carlo Methods for Computing Bayes Factors: A Comparative Review" (2001, Vol. 96, pp. 1122-1132)] analyzed the tabulated data on compressive strength parallel to the grain versus resin-adjusted density for specimens of radiata pine. The data are shown below. Compressive Compressive Density Density

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An article in the Journal of the American Statistical Association ['Markov Chain
Monte Carlo Methods for Computing Bayes Factors: A Comparative Review"
(2001, Vol. 96, pp. 1122-1132)] analyzed the tabulated data on compressive
strength parallel to the grain versus resin-adjusted density for specimens of radiata
pine. The data are shown below.
Compressive Density
Compressive Density
Strength
Strength
3040
29.2
3840
30.7
2470
24.7
3800
32.7
3610
32.3
4600
32.6
3480
31.3
1900
22.1
3810
31.5
2530
25.3
2330
24.5
2920
30.8
1800
19.9
4990
38.9
3110
27.3
1670
22.1
3160
27.1
3310
29.2
2310
24
3450
30.1
4360
33.8
3600
31.4
1880
21.5
2850
26.7
3670
32.2
1590
22.1
1740
22.5
3770
30.3
2250
27.5
3850
32
2650
25.6
2480
23.2
4970
34.5
3570
30.3
2620
26.2
2620
29.9
2900
26.7
1890
20.8
1670
21.1
3030
33.2
2540
24.1
3030
28.2
a. Fit a regression model relating compressive strength to density.
b. Test for significance of regression with a = 0.05.
c. Estimate o for this model.
d. Calculate R² for this model. Provide an interpretation of this quantity.
e. Prepare a normal probability plot of the residuals and interpret this display.
f. Plot the residuals versus ŷ and versus x. Does the assumption of constant
variance seem to be satisfied?
Transcribed Image Text:An article in the Journal of the American Statistical Association ['Markov Chain Monte Carlo Methods for Computing Bayes Factors: A Comparative Review" (2001, Vol. 96, pp. 1122-1132)] analyzed the tabulated data on compressive strength parallel to the grain versus resin-adjusted density for specimens of radiata pine. The data are shown below. Compressive Density Compressive Density Strength Strength 3040 29.2 3840 30.7 2470 24.7 3800 32.7 3610 32.3 4600 32.6 3480 31.3 1900 22.1 3810 31.5 2530 25.3 2330 24.5 2920 30.8 1800 19.9 4990 38.9 3110 27.3 1670 22.1 3160 27.1 3310 29.2 2310 24 3450 30.1 4360 33.8 3600 31.4 1880 21.5 2850 26.7 3670 32.2 1590 22.1 1740 22.5 3770 30.3 2250 27.5 3850 32 2650 25.6 2480 23.2 4970 34.5 3570 30.3 2620 26.2 2620 29.9 2900 26.7 1890 20.8 1670 21.1 3030 33.2 2540 24.1 3030 28.2 a. Fit a regression model relating compressive strength to density. b. Test for significance of regression with a = 0.05. c. Estimate o for this model. d. Calculate R² for this model. Provide an interpretation of this quantity. e. Prepare a normal probability plot of the residuals and interpret this display. f. Plot the residuals versus ŷ and versus x. Does the assumption of constant variance seem to be satisfied?
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