Python Question:

Problem 03 Cummulative Density Function (cdf) of exponential distributions Note that the Cummulative Density Function of exponential distribution with parameter , >0 looks like this 0, otherwise Your code should be able to do the following: Given , and an array arr; your function can return an array of values F(x: ) for each x E arr eg: F(I-1,1],0.5) should return [0 0.69673467014368329] of type numpy.ndarray For fixed arr np.arange(50)/50 For = 0.5-,-1, ~1.5 , save the values F(arr; ) to a new variable vi, and print out their mean. you may need np.exp() # your function here def exp_cdf(arr,lam): return np.array(LI) # please don't change the value of arr or Lambdai's arr = np.arange(50)/5 lambda 0.5 yl exp-cdf(arr, lambda!) lambda2 = 1 y2 exp-cdf(arr, lambda2) lambda3 = 1.5 #print the mean of yl, the mean of y2, the mean of y3 print()