2. (a) Let us consider a full model of a balanced (all t treatments have equal...
Please help! (a) Let us consider a full model of a balanced (all t treatments have equal number of observations r) CRD design with t treatments and r replications of each treatment, hence having n-rt observations. 2. i. Minimizing sum of square error Δfull (μ'Ti) -Σι-1 Σ-1 (Vi,- μ-Ti)2 with respect to μ and Ti find the least square estimators of μ and Ti as μ and Ti. Hint: Take derivative of the objective function with respect to μ and...
2. (a) Let us consider a full model of a balanced (all t treatments have equal number of observations r) CRD design with t treatments and r replications of each treatment, hence having n rt observations. . Minimizing sum of square error Δ/u114%)-ΣΊ ΣΊ (Vij-μ-%)2 with respect to μ and Ti find the least square estimators of μ and Ti as μ and T. Hint: Take derivative of the objective function with respect to μ and Ti and equate then...
2. Use the data in hpricel.wfl uploaded on Moodle for this exercise. We assume that all assump- tions of the Classical Linear Model are satisfied for the model used in this question. (a) Estimate the model and report the results in the usual form, including the standard error of the regression. Obtain the predicted price when we plug in lotsize - 10, 000, sqrft - 2,300, and bdrms- 4; round this price to the nearest dollar. (b) Run a regression...
We consider a multiple linear regression model with LIFE (y) as the response variable, and MALE (x1), BIRTH (x2), DIVO (x3), BEDS (x4), EDUC (x5), and INCO (x6), as predictors. "STATE" "MALE" "BIRTH" "DIVO" "BEDS" "EDUC" "INCO" "LIFE" AK 119.1 24.8 5.6 603.3 14.1 4638 69.31 AL 93.3 19.4 4.4 840.9 7.8 2892 69.05 AR 94.1 18.5 4.8 569.6 6.7 2791 70.66 AZ 96.8 21.2 7.2 536.0 12.6 3614 70.55 CA 96.8 18.2 5.7 649.5 13.4 4423 71.71 CO 97.5...