Find the following for multiple linear regression

(a) Set three random vectors of 1000 random numbers as follows: x1: from Unif(0,5), x2: from Binom(70,0.2), and x3: from Exp(1). Define y = x1 + 4*x2 + 8*x3 + 10 + Err, where Err ~ N(0,sd=10).

(b) Generate a dataframe df containing these four variables and create scatterplots of all pairs of these four variables.

(c) Generate a multiple regression model for y as a linear function of x1, x2, and x3 and print its summary.

(d) Run your entire code for parts (a)-(c) several times and keep an eye at summary() outputs. Which of the variables has the 'slope' that has the largest variance? Explain which of the summary() parameters describes this?