## Lesson 18: Monte Carlo Simulation

April 13, 2016

Wed Apr 13

Review:

- Multiple Regression in Python

Presentation:

- Monte Carlo Simulation
- Resources
- Sample Code

Assignment:

- Create a simple Monte Carlo Simulation with Python
- Simulate a simple Dice Game:
- Roll 2-7, lose
- Roll 8-12, win
- Start with $100
- bet $1 per roll (win pays $1, loss takes $1 bet)
- roll 100 times and find ending balance (could be negative)
- simulate 100 outcomes (10,000 total rolls of the dice)

- Report the mean, median, and standard deviation of your final balances
- Repeat using 1,000 rolls per outcome (100,000 total rolls of the dice) and report the mean, median and standard deviation of final outcomes

[highlight color=”options: yellow, black”]Here’s some python code to help you get going (and plain text below): [/highlight]

import random

def rollDice():

roll = random.randint(1,6)

return roll

j = 0

rollcount = 0

rolls = []

while j < 100:

i = 0

j = j + 1

while i < 100:

i = i + 1

result = rollDice()

rolls.append(result)

rollcount += 1

import scipy

mr = scipy.mean(rolls)

print(“Total rolls = “)

print rollcount

print(“Mean roll = “)

print mr

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