Developed by Andy Rundquist  Published October 3, 2016
Subject Area  Mathematical / Numerical Methods 

Level  First Year 
Available Implementations  Mathematica, Python, and Easy Java Simulations 
Learning Objectives 
Students will be able to:
* Generate normally distributed random numbers (**Exercise 1**)
* Plot histograms. Calculate mean, median, and standard deviation for a distribution. Generate a new distribution from previously generated random numbers. (**Exercise 3**)
* Compare the analytical (calculus) approach to the Monte Carlo approach (**Exercises 2 and 3**)

Time to Complete  30 min 
These exercises are not tied to a specific programming language. Example implementations are provided under the Code tab, but the Exercises can be implemented in whatever platform you wish to use (e.g., Excel, Python, MATLAB, etc.).
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Credits and Licensing
Andy Rundquist, "Monte Carlo error propagation," Published in the PICUP Collection, October 2016, https://doi.org/10.1119/PICUP.Exercise.MCerrorprop.
DOI: 10.1119/PICUP.Exercise.MCerrorprop
The instructor materials are ©2016 Andy Rundquist.
The exercises are released under a Creative Commons AttributionNonCommercialShareAlike 4.0 license