This question is data analysis with R. Could you please little explain because I am new for R program? Thank you.

Data Analysis with R In R, using the data set prostate within the package "faraway", analyze the data by answering the questions below. Prostate data has 97 subjects and 9 variables (please check this information with using the line of code 'help(prostate)'). Let lpsa, log prostate specific antigen, be a response variable and we have proposed two models: Model 1: Ipsa ~ leavol + lweight + age + lbph + svi + lep + gleason + pgg45 Model 2: Ipsa ~ Icavol + lweight + age + lbph + svi Study the model fit of the two models and diagnose for any undesired conditions. a. Check for high leverage points. For the two models, how many leverage points are there? What are the hi values? Do the two models share the same leverage points? b. Provide the half-norm plots that plot absolute values of the residuals against the leverage, h;, for the two models. Comment on the outliers. c. Compute five studentized error values in decreasing order for the two models. How different are they? d. Compute cook's distance and compare them. How many highly influential points are there? e. Using the function 'plot()' provide the residual plots for the two fits. Can you locate the high-leverage points, influential points and outliers? f. Conduct Breusch-Pagan test and Shapiro-Wilks test and comment on the het- eroscedasticity and the normality of the residuals. g. Which model would you choose? Justify