You have 2 explanatory variables x1 and x2 below, and a response variable y. Ple

Question

You have 2 explanatory variables x1 and x2 below, and a response variable y. Please fit the least square hyperplane. x1-c(2.3, 3.2, 1.3, 0.3, 4.1,2.4, 3.6,8.6,2.3,4.5, 3.8,2.6, 1.1, 2.8, 1.4,2.4,0.9, 1.4, 4.4,5) x2-c(4.5, 4.7, 4.8, 6, 1.5, 2,5.7, 11.9,3.6,2.8, 2.3, 3.2,5,1.7,3.4,4.9, 3.3, 4.3, 6,2.4) and y-c(19.2, 22.4, 17, 15.1, 17.9, 13.2, 24.6, 52, 16.1,21.9,18.4, 16.4, 16.9,15.7, 9.5,20.7, 12.4, 16.6, 28, 21.8) Part a) The slope of x1 for the least square hyperplane is p1-2.9597 Part b) The value of largest absolute residual is: 4.1524 Part c) Based on Cook's distances or the dfit statistics, from ls.diag0 applied to an Im object, does the observation with the largest absolute residual correspond to an influential observation? (Enter either Yes or No) Yes Part d) Check the output of Cook's distances or the dfit statistics, and check on how your largest absolute residual compares with the other residuals. Then determine the best answers below on interpretations of influential observations. Possibly more than one item is correct. A. Influential observations should be deleted B. An influential observation need not have an extreme residual C. The number of influential observations can be 0,1,2,., or n-p-1, where p is the number of explanatory variables D. Influential observations have heavy influence on some B E. In general, influential observations are extreme residuals (outliers) F Influential observations sometimes are in the extremes of the space of explanatory variables G. None of the above

Explanation / Answer

Answer is (A), (E) and (D)

A)Influential observations should be deleted

D)Influential observations are heavy influence on Bs

E)Influential Onservations are extrem outliers.

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