please help must be in python

2. The function scipy.stats.linregress(x,y) performs a linear regression of y on s. It returns five values: the slope, intercept, correlation, p-value against the null hypothesis that the slope is zero, and the standard-error. You can extract the slope and intercept as follows m, b, r, p, SE-scipy. stats. Inregress(x,y) In this exercise we are only interested in finding m and b and making a plot of the line y=mx + b You can plot a data set of r points and y points as dots and the best fit line using plt.plot and plt.scatter as follows: m,b,r,p, SE-scipy.stats.linregress (x,y) plt.scatter(x,y) plt, plot( [xmin, xmax], [m* xmin+b, m#xmax+D ]) Here xmin and xmax are the left and right endpoints of the line The following table contains four data sets: Set 2 Set 3 Set 4 10.00 8.04 10.00 9.14 10.00 7.46 8.00 6.58 8.00 6.95 8.00 8.14 8.00 6.77 8.00 5.76 13.00 7.5813.00 8.74 13.00 12.74 8.00 7.71 9.008.81 9.00 8.77 9.00 7.1 8.00 8.84 11.00 8.33 11.00 9.26 11.00 7.81 8.00 8.47 14.00 9.9614.00 8.10 14.00 8.84 8.00 7.04 6.00 7.246.00 6.13 6.00 6.08 8.00 5.25 4.00 4.26 4.00 3.10 4.00 5.39 19.00 12.50 12.00 10.84 12.00 9.13 12.00 8.15 8.00 5.56 7.00 4.82 7.00 7.26 7.00 6.42 8.00 7.91 5.00 5.68 5.00 4.74 5.00 5.73 8.00 6.89 In a single figure that has a two by two grid, plot each of these data sets (as a scatter plot, using plt.scatter), one data set on each grid Plot of Data Plot of Data Set 1 Plot of Data Plot of Data Set 3 Set 2 Set 4 Overlay each scatter plot with the appropriate line y mxb using plt.plot Compare your results for the slope and intercept (and the correlation, if you have taken a statistics class), writing your conclusions in a markdown cell. Do you think linear regression is an appropriate description of any of this data sets. If so why, and if not why not