Monte Carlo Simulations and Probabilistic Techniques

 
Monte Carlo Simulations
by Gio
 
Other
 
0
 
Basic Principle: Monte Carlo Method
 
The Monte Carlo Method is the approach (methodology) of using
randomness to describe problems that may have a deterministic
solution
 
The Law of Large Numbers (LLN) states that with an increase in the
number of measurements the expected value grows to equal the
average value
 
A Pseudo-Random Number Generator is an algorithm for generating
numbers that appear reasonably random in sequence
 
 
1
 
Law of Large Numbers
 
2
 
Pseudo Random Number Generator
 
Approximate randomness
 
Probability distributions [0, 1]
 
3
 
Monte Carlo Steps
 
Step 1: Define the probability space and the points within that space; use a large
number of points to define the space
 
Step 2: Define the conditions of the problem that constrains the space
 
Step 3: Discriminate between the points that reside within the constraints of the
problem and those that do not
 
Step 4: Use the points that reside within the constraints to define the space of the
solution
 
Important: The greater the number of points, the greater the accuracy of the
simulation
 
4
 
Colab Exercises
 
Conditional Probability
 
Basic Geometry
 
Calculus
 
5
 
Conditional Probability
 
Which combination of numbers, on average, give a larger value; three
numbers between 1-4 or two number between 1-6? Always double
the lowest number in each combination.
 
 
 
 
 
 
 
6
 
Basic Geometry
 
Determine the area of basic geometric shapes without using the area
formulas for those shapes
 
Relative areas
 
7
 
 
Calculus
 
Determine the area under the curve without integrating
 
Random sampling
 
8
 
Thank you!
 
9
Slide Note

https://colab.research.google.com/drive/1D7iUKkEnrlmknKKrVC4VYUpYZx54ex9l?usp=sharing

https://colab.research.google.com/drive/144Exi-nGqhckvsFfUMzkts5S0UUwbZwp?usp=sharing

Embed
Share

Dive into the world of Monte Carlo simulations and probabilistic methods, understanding the basic principles, the Law of Large Numbers, Pseudo-Random Number Generators, and practical Monte Carlo steps. Explore topics like conditional probability, basic geometry, and calculus through engaging exercises. Uncover the convergence of averages, the concept of randomness, and more in this comprehensive exploration.

  • Monte Carlo Simulations
  • Probabilistic Techniques
  • Law of Large Numbers
  • Pseudo-Random Numbers
  • Conditional Probability

Uploaded on Jul 30, 2024 | 3 Views


Download Presentation

Please find below an Image/Link to download the presentation.

The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. Download presentation by click this link. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.

E N D

Presentation Transcript


  1. Other Monte Carlo Simulations by Gio 0

  2. Basic Principle: Monte Carlo Method The Monte Carlo Method is the approach (methodology) of using randomness to describe problems that may have a deterministic solution The Law of Large Numbers (LLN) states that with an increase in the number of measurements the expected value grows to equal the average value A Pseudo-Random Number Generator is an algorithm for generating numbers that appear reasonably random in sequence 1

  3. Law of Large Numbers 1 die VS. 30 dice VS. 103 dice Convergence of Average and Expected Value 2

  4. Pseudo Random Number Generator Approximate randomness Probability distributions [0, 1] 3

  5. Monte Carlo Steps Step 1: Define the probability space and the points within that space; use a large number of points to define the space Step 2: Define the conditions of the problem that constrains the space Step 3: Discriminate between the points that reside within the constraints of the problem and those that do not Step 4: Use the points that reside within the constraints to define the space of the solution Important: The greater the number of points, the greater the accuracy of the simulation 4

  6. Colab Exercises Conditional Probability Basic Geometry Calculus 5

  7. Conditional Probability Which combination of numbers, on average, give a larger value; three numbers between 1-4 or two number between 1-6? Always double the lowest number in each combination. 6

  8. Basic Geometry Determine the area of basic geometric shapes without using the area formulas for those shapes Relative areas 7

  9. Calculus Determine the area under the curve without integrating Random sampling 8

  10. Thank you! 9

Related


More Related Content

giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#