Monte Carlo simulations allow us to face up to uncertainty, rather than hide from it. In this session, I describe the steps in a simulation, starting with choosing the input variables that you will be using probability distributions (rather than point estimates), moving on to choosing the right distributions & parameters for these variables, ending with a reading of what the simulation output tells us about the output variable. I use a valuation of Apple from 2016 to illustrate the process.
Slides: http://www.stern.nyu.edu/~adamodar/pd...
Post class test: http://www.stern.nyu.edu/~adamodar/pd...
Post class test solution: http://www.stern.nyu.edu/~adamodar/pd...
Webpage for statistics class: http://people.stern.nyu.edu/adamodar/...
YouTube Playlist for this class:    • Statistics 101