2 8595 2 3 x1 93265 12978 170 12736 we

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Unformatted text preview: in auction price of a 170-year-old grandfather clock, y, for each additional bidder. ˆ 2 ≈ 85.95 ˆ ˆ 2 + 3 x1 ≈ – 93.265 + 1.2978 ⋅ 170 ≈ 127.36 We estimate that the auction price of a grandfather clock will increase by about $85.95 for every additional bidder. We estimate that the auction price of a 170-year-old clock will increase by about $127.36 for every additional bidder. > clocks.dat$y[17] = 1131 – creating an outlier > clocks.fit3 = lm(y ~ x1 + x2 + x1x2, data=clocks.dat) > summary(clocks.fit3) Call: lm(formula = y ~ x1 + x2 + x1x2, data = clocks.dat) Residuals: Min 1Q -783.43 -75.51 Median -11.01 3Q 125.33 Max 285.70 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -512.8102 665.8601 -0.770 0.4477 x1 8.1651 4.5847 1.781 0.0858 . x2 19.8877 67.4376 0.295 0.7702 x1x2 0.3196 0.4790 0.667 0.5101 --Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 200.6 on 28 degrees of freedom Multiple R-Squared: 0.7292, Adjusted R-squared: 0.7002 F-statistic: 25.13 on 3 and 28 DF, p-value: 4.277e-08 > > > > > > > > > X = cbind(rep(1,32),clocks.dat$x1,clocks.dat$x2,clocks.dat$x1*clocks.da...
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