Generate Common Distributions

By for October 19, 2016

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This generates data for uniform, normal, log normal or logistic distribution to be used for sensitivity analysis
This experiment generates data using a user selected distribution such as uniform, normal, logistic and lognormal. For example, user may want to do a montecarlo simulation over the model against normal curve and this module can help generate this data ### Module Configuration ### This module expects user to select a distribution and provide: - Mean - This is the desired mean for the data generated for user selected distribution. - Standard Deviation - This is the desired standard deviation for the data generated for user selected distribution - Min - This is used only for exponential and gamma for creating data with values greater than this value - Max - This is used for exponential and gamma for creating data with values less than this value - Rows - This is used as input on how much data is created and shape the dataframe - Columns - This is used as input on how much data is created and shape the dataframe - Type of distribution - This is where user provides what type of distribution should be used for creating dataset - Seed - This is used as a seed for randomization of the data ![](http://neerajkh.blob.core.windows.net/images/CommonDistroModuleConfigCapture.PNG) ### Sample Output Dataset ### The figure below shows the dataset generated by the algorithm along with the distribution of the generated data ![](http://neerajkh.blob.core.windows.net/images/CommonDistroDataCapture.PNG) ![](http://neerajkh.blob.core.windows.net/images/CommonDistroPlotCapture.PNG) ### Source Code### The source code for this file is located here - [https://gist.github.com/nk773/534e17588e2013fb98fde7a26d42eb72](https://gist.github.com/nk773/534e17588e2013fb98fde7a26d42eb72)