Problem 2: Rolling dice

Now that we can roll a single die, we want to see the probabilities of rolling any possible number when we have Ndice rolled simultaneously.

To Do:

Write a new python file called Dice.py that imports rollFairDie and rollUnFairDie from Die.pyand includes a function called rollDice(N=1), where N is a keyword argument that specifies the number of dice to be rolled. rollDice should call rollFairDie N times and return the total score by summing the score of each die.

In a separate file called HW1SP22_Prob2.py, write and call a main() function that specifies the number of dice (n) and calls the function rollDice(N=n) 1000 times and then outputs the probability for each possible score to the screen as:

Probability of rolling a 3: 0.xxx

Etc.

(note: for 3 dice, min score =3, max score =18, for 4 dice, min score = 4, max score = 24, etc.)

Problem 3: A continuous random variable

Description: To simulate real-wold behavior of systems, we often must produce normally distributed values for a property of a system (e.g., the average mass of a pebble in a pile of gravel). Here, you must produce a program that yields an array of data that is normally distributed around a specified mean () and standard deviation (). (Note: if I use a random number generator to produce a uniformly distributed value between 0 and 1, we can use this value as the dependent variable on a cumulative distribution function and find the independent variable value (x) corresponding to this probability. The values of x will be normally distributed.) Your program should output an array of size N drawn from normally distributed population. You should do this work in a file called HW1SP22_Prob3.py

Hint: from the module random, you should investigate the use of the function normalvariate().