2. The goal in this problem is to reproduce the experiment that John D. Cook describes in his post Com- paring three methods of computing standard deviation. You can implement your functions in Python or in MATLAB. You are welcome to look at Wikipedia's entry on Algorithms for calculating variance for guidance, but do not simply cut-and-paste their code. Do not use pre-existing methods/functions for computing the variance (e.g., var in MATLAB or numpy.var in Python) although you can use standard idioms for computing sums without loops (e.g., sum in MATLAB or numpy. sum in Python) You will construct three functions that implement the computation of the variance s2 of a discrete set of values by three distinct methods. . Each function should accept a vector x as input and return the variance computed appropriately. . Include relevant documentation (e.g., a docstring in Python or an H1 line in MATLAB) to make the usage clear and to explain the algorithm in each. tion so much as one that implements the correct recurrences "direct method" for computing the variance of a vector of values, i.e, Concern yourself with accuracy more than efficiency; don't worry about making the fastest solu (a) Construct a (Python or MATLAB) function that implements the computation of what Cook calls the P7 where -(1)-1 is the mean of the values 1 This method requires two passes through the data: one to compute the mean and a second to com deviations from the mean. pute the sum of the squared