Developed by Andy Rundquist - Published October 3, 2016
|Subject Area||Mathematical / Numerical Methods|
|Available Implementations||Mathematica, Python, and Easy Java Simulations|
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.
The instructor materials are ©2016 Andy Rundquist.
The exercises are released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 license