QUESTION 1:

QUESTION 2:

PLEASE WRITE THE CODE IN PYTHON. I WILL RATE. THANK YOU!

#All packages needed import numpy as np import scipy.special as spsp import scipy.stats as spspt import matplotlib.pyplot as plt &matplotlib inline It is suggested that one of the algorithms to generate y ~ Unif(a, b) is to do the following: Generate a random number x Convert this random number x to a sample y using (b a)y + a Construct a function with a, b, and N as the arguments. This function should return an array of N number of random samples y based on the algorithm listed. Run this function with a = 5, b = 10, and N = 1000 and visualize the distribution of the samples. In the same plot, plot the targeted theoretical distribution. . Based on the plot, comment on whether this algorithm seems to be correct. Run the function above with a = 10,6 = 15, and N = 1000. Based on the 1000 y samples we generated, construct the 90% confidence interval for the population mean of the distribution y is generated from. [] #All packages needed import numpy as np import scipy.special as spsp import scipy.stats as spspt import matplotlib.pyplot as plt &matplotlib inline It is suggested that one of the algorithms to generate y ~ Unif(a, b) is to do the following: Generate a random number x Convert this random number x to a sample y using (b a)y + a Construct a function with a, b, and N as the arguments. This function should return an array of N number of random samples y based on the algorithm listed. Run this function with a = 5, b = 10, and N = 1000 and visualize the distribution of the samples. In the same plot, plot the targeted theoretical distribution. . Based on the plot, comment on whether this algorithm seems to be correct. Run the function above with a = 10,6 = 15, and N = 1000. Based on the 1000 y samples we generated, construct the 90% confidence interval for the population mean of the distribution y is generated from. []