Time: 2 weeks

Team: 2

Language: Python

Steven is a suit-seller in Mississippi. Once a year, he gets rid of his unsold stock, selling separately jackets and trousers, at $10, $20, $30, $40 and $50. He’d like to know how much each piece of clothing is likely to yield (expected value and variance). Steven gave his statistician friend a mission: to deduce from his past results the probability to sell a $x jacket and $y trousers together.

It appears that the probability is defined by the following formula (a and b being integers greater than 50, depending on the economic climate):

(a−x)(b−y)(5a−150)(5b−150)

Let’s call X, Y and Z, respectively, the random variables that represent “the price of a sold jacket”, “the price of sold trousers” and “the price of a sold suit”. Given the values of *a and b, your software must print:

• an array summing up the joint law of(X, Y), and the marginal laws of X and Y
• an array summing up the law of Z
• expected values and variances of X, Y and Z

>> ./202unsold -h
USAGE
	./202unsold a b

DESCRIPTION
	a	constant computed from the past results
	b	constant computed from the past results

Author Corentin COUTRET-ROZET and PATRICIA MONFA-MATAS