Lesson 9: Intro to Monte Carlo Simulation

November 3, 2025

Review:

• Multiple Regression exam results

• 

• Exam solutions
• Used car pricing model submissions

Presentation:

• Probability
  • Topic worthy of its own course
• Simulation
  • Random phenomenon
    • Individual outcomes are uncertain
    • Regular distribution of outcomes in large number of trials
  • Random number generation and stochastic processes
  • Discrete and Continuous (we’ll start with discrete)
• Coin Toss Simulation
  • Demonstrate Coin Toss Simulation in Sheets
• Dice Roll Simulation
  • Demonstrate Dice Roll Simulation in Sheets in Sheets
  • Lucky 7 game
    • Roll a 7, win bet
    • Roll anything else (other than a 7), lose bet

Assignment:

• Replicate the Coin Toss simulation
  • 200 coin tosses (instead of 32)
  • reproduce the graph (showing 200 tosses)
• Create a “Roll 2 Dice” simulation
  • 100 rolls (instead of 32)
  • Roll 2 Dice instead of only 1
  • Be sure the probability distribution is the same as actually rolling 2 Dice.
• Create a “Lucky 7” simulation
  • Roll 2 Dice
  • If you roll a 7, you win
  • If you don’t roll a 7, you lose
  • Track the number of wins and losses
• Create a “Simple Craps” simulation
  • Roll 2 Dice
  • If you roll a 7 or 11, you win $10
  • If you roll a 2, 3 or 12, you lose $5
  • If you roll anything else (i.e., 4, 5, 6, 8, 9, 10), it’s a “push” or a tie and you don’t lose or win $$.
  • Set up a scoring system to keep track of how much $$ you win or lose.