Consider the following distributions:
• A continuous uniform distribution between [10, 20]
• A discrete distribution, that returns the following values with the given probability
Value
Probability
5
0.2
15
0.6
20
0.2
• An exponential distribution with average 15
• An hyper-exponential distribution with two stages, characterized by (l1 = 0.1, l2 = 0.05, p1 = 0.5)
• An hypo-exponential distribution with two stages characterized by (l1 = 0.1, l2 = 0.2)
• An Hyper-Erlang characterized by the following branches, number of stages, rates and selection probabilities
Num. stages (k)
Rate (l)
Probability
1
0.02
0.1
2
0.2
0.4
3
0.25
0.5
For each distribution, generate N = 500 samples using the techniques seen during the course (you can use the function that returns a uniformly distributed random number of your tool), and plot their approximated CDF on the same graph. Also compute, for each of them, the average and the C.V. starting from the generated samples.
