Via Python 1. Generate a list of 2000 Gaussian distributed random numbers with mean 2 and standard deviation 3. 2. Make a scatter plot random number versus list index number. 3. Create a function meanpstd(lst) for computing the mean and the population standard deviation of the random numbers (use one and the same loop for computing both). Use the alternative formula std = sqrt(x2>x2), where x2> is the mean of the squared random numbers and x is the mean. The beginning and the end of the meanpstd(lst) function should be defined as shown here: def meanpstd(lst): lstmean =0.0 lststd =0.0 \# Return 2 variables. return lststd, lstmean Add the calculations for lststd and lstmean where the three dots (...) are. 4. Use the following statement to write both calculated values into the variables std and mean: std, mean =altpstd( data ) 5. Print the values of std and mean. 6. Add comments to the program explaining briefly what the code is doing