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Consider a linear model with the following mean response function: E{Y} = Bo+ PIXI + 82 12 + B313. We fit the model with R,

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Consider a linear model with the following mean response function: E{Y} = Bo+ PIXI + 82 12 + B313. We fit the model with R, and displayed some statistics concerning the fit. > mod vcov (mod) (Intercept) x1 x2 x3 (Intercept) 312.677879 -11.51016043 -1.15228722 -4.16863215 x1 -11. 510160 0. 81923112 -0. 05984168 0.01443894 x2 -1. 152287 -0. 05984168 0. 09546028 -0.01456972 x3 -4. 168632 0. 01443894 -0. 01456972 0. 18199326 > mod$df . residual [1] 16 (a) Give the value of n? In other words, there are how many observations? (b) Give an estimate for e = 1 - 82, and compute its estimated standard error. (c) Give a 95% confidence interval for e from (b). (d) We fit another linear model below. Give the estimated mean response function. > modo summary (mod) $sigma [1] 11. 23585 summary (mod0) $sigma [1] 62.51839 Formulate the hypotheses being tested. Compute the observed value of the F-test statistic, and write-down the p-value symbolically

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