Please help with this Regression Analysis assignment as much as you can. The answers should be in R-coding language.

Any help is greatly appreciated! :)

Q2. The dataset trees contains measurements of Girth (actually, tree diameter) in inches, Height in feet, and Volume of timber (in cubic feet) of a sample of 31 felled black cherry trees. The following commands can be used to read the data into R. The dataset can be accessed under the name trees. # the dataset "trees" is contained in the R package "datasets" require(datasets) trees (2a). (1 pt) Briey describe the dataset trees, i.e., how many observations (rows) and how many variables (columns) are there in the dataset? What are the variable names? (2b). (2 pts) Use the pairs function to construct a scatterplot matrix of the logarithms of Girth, Height and Volume. (2c). (2 pts) Use the cor mction to determine the correlation matrix for the three (logged) variables. (2d). (2 pts) Are there missing values? (2e). (2 pts) Use the lm function in R to t the multiple regression model, log Volume; = o + 1311012; Gil'thi, + 52 103 Height, + 511 and print out the summary of the model t. (21). (2 pts) Create the design matrix (i.e., the matrix of predictor variables), X, for the model in (2e), and verify that the least squares coefcient estimates in the summary output are given by the least squares formula: (XTX)1XTy. (2g). (3 pts) Compute the predicted response values from the tted regression model, the residuals, and an estimate of the error variance Var(s) = a2