Writing everything in python, use

from scipy.stats import multivariate_normal from IPython.display import Image import random import numpy as np import pandas as pd import scipy.stats as st import matplotlib.pyplot as plt

x=np.array([1,2,3]) y=np.array([4,5,6]) def f(x, y):

Question 1 Let ? ? x2 r E R2 be a two dimensional vector drawn from a distribution. Also assume we have collected A previous experiment has shown the distribution of this data is of the form: samples, X- xi 12, from the distribution. Equation 1 ??-1 1 01,and ?2 =10 2 2 D also p0.3 and p2 0.7 Part 1 Write a python scrip that computes p(x). The function should compute the the probablity for this input p(np.array([1,2,3]),np.array (I4,5,6]). Run your function by inputting np.array([1.2,3),np.array((4,5,6 ad print out the three probabilities associted with [1,4]. 12,5], and [3,6] Note that you are only allowed to use the multivariate_normal function from scipy.stats. You won't get any credit if you use any other library or function. Also you are not allowed to use any loops in your code. Question 1 Let ? ? x2 r E R2 be a two dimensional vector drawn from a distribution. Also assume we have collected A previous experiment has shown the distribution of this data is of the form: samples, X- xi 12, from the distribution. Equation 1 ??-1 1 01,and ?2 =10 2 2 D also p0.3 and p2 0.7 Part 1 Write a python scrip that computes p(x). The function should compute the the probablity for this input p(np.array([1,2,3]),np.array (I4,5,6]). Run your function by inputting np.array([1.2,3),np.array((4,5,6 ad print out the three probabilities associted with [1,4]. 12,5], and [3,6] Note that you are only allowed to use the multivariate_normal function from scipy.stats. You won't get any credit if you use any other library or function. Also you are not allowed to use any loops in your code