Suppose we have the following dataset with one response Variable y and two predictor variables Ni and No: 20 y X X 140 60 22 155 62 25 159 67 24 179 70 20 192 71 15 200 72 14 212 75 215 78 14 11 A) Calculate the intercept b0, slope b1, and b2., and write down the estimated regression equation. B) Define the best hypothesis and predict the value of x1=74, x2=19. Show the computation steps clearly. C) How to Interpret a Multiple Linear Regression Equation D) Compute the squared error E and plot the error curve. Also, mark the point of global minima on the plotted error curve E) Gradient Descent and Stochastic Gradient Descent are very similar in that they both iteratively update the parameter vector based on the gradient of a function. Describe either in words how they differ. F) Write Python code for the regression model to solve this problem? (Use only the libraries of the Numpy and pandas Matlabplot) Good Luck!