In [ ]: *** Lood Libraries import numpy as np from scipy.stats import norm import matplot lib.pyplot as plt Workspace 1: Create normally distributed data Reference for standard deviation to mayorg/doc/stable/reference/generated/my.sid html 1 Set the number of points in your dataset (nsamples) to 10 2 Create appropriate variables for the height of men (use, mu-177 and sigma-4) -- use a similar notation as is used for the women 3. Calculate the mean and standard deviation of the two distributions 4 What is the meaning of mu_w and sigma_w? You may have to increase the sample size (nsamples) to eg 1000 to better understand what the different variables represent ---reset to 10 when you are done with this step ]: ### Create normally distributed data ### Exercise 1: nsamples - 1 ### Number of points/samples in normal distribution ## Normal distribution (women) mu w - 170 sigma_w - 5 height_w - mu_w - sigma_w*np.random.randn(nsamples) ### (Ex 4) what is this? ### (Ex 4) what is this? www height in cm # Normal distribution (men) ## Exercise 2: mum- sigma_m - height_m - mu_m.sigma_m np.random.randn(nsamples) , # Exercise 3: ## Calculate the mean and standard deviation of the normal distributions defined above #* (1.e., variables heigth_w and height_) ** Find the appropriate reference for how to calculate the mean (hint, google is your friend here...) ** Reference for standard deviation * https:/umpy.org/doc/stable/reference/generatedumpy.std.html ** Calculate mean and standard deviation of height_w