3. (R programming) The weight and systolic blood pressure of 26 randomly selected males in the age group 25-30 are in the attached CSV file. We fit a simple linear regression model relating systolic blood pressure (y) to weight (x). (55 points) (a) Draw the scatterplot of the data points with R function plot. Add the linear regression line using the R function abline after plot. (10 points) Note: Present two plots: one is a scatterplot only and the other is a setterplot with the regression line. 'b) Find the coefficient of determination (R") and compute the total sum of squares (SST). Using the two, compute the regression sum of squares (SSR). (15 points) (c) Find the 99 % confidence interval on (i) the slope and the intercept, (ii) the mean response at x = 160, 180, 200. (10 points) (d) Find the 99 % prediction interval on 26 future observations whose weights are identical to the males' in the dataset. (5 points) Hint: Create a data. frame whose x values are all the 26 males' weights. (e) Merge the data. frame of the 26 data points with the outcome object in (d) using R function cbind. Name the merged data. frame of size 26 x 5 pred. bp. Draw the confidence interval curve using the commands below. library ("ggplot2") p