3.72 C - -0.30732 -0.02940 0.03045 0.05943 0.17014...

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Sheet1 Page 1 > x=c(-262,-265,-256,-267,-270,-272,-272.4,-272.7,-272.8,-272.9) > x [1] -262.0 -265.0 -256.0 -267.0 -270.0 -272.0 -272.4 -272.7 -272.8 -272.9 > y=c(.315,.202,.204,.620,.715,.935,.957,.906,.985,.987) > cbind(x,y) x y [1,] -262.0 0.315 [2,] -265.0 0.202 [3,] -256.0 0.204 [4,] -267.0 0.620 [5,] -270.0 0.715 [6,] -272.0 0.935 [7,] -272.4 0.957 [8,] -272.7 0.906 [9,] -272.8 0.985 [10,] -272.9 0.987 > g=lm(y~x) > summary(g) Call: lm(formula = y ~ x) Residuals: Min 1Q Median 3Q Max
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Unformatted text preview: -0.30732 -0.02940 0.03045 0.05943 0.17014 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -13.490347 2.073772 -6.505 0.000187 *** x -0.052829 0.007728 -6.836 0.000133 ***---Signif. codes: 0 ¡¥***¡¦ 0.001 ¡¥**¡¦ 0.01 ¡¥*¡¦ 0.05 ¡¥.¡¦ 0.1 ¡¥ ¡¦ 1 Residual standard error: 0.1333 on 8 degrees of freedom Multiple R-squared: 0.8538, Adjusted R-squared: 0.8356 F-statistic: 46.73 on 1 and 8 DF, p-value: 0.0001329...
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This note was uploaded on 06/06/2011 for the course STAT 4230 taught by Professor Yin during the Spring '11 term at University of Georgia Athens.

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