You need to know if the data is normally distributed before doing any analysis on it.
Create histograms for every column and compare it to a normal distribution or bell curve. My code outputs this bell curve on the graph.
LauraM.dev lauracodecreations
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/ Normal_Distribution.md
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May 1, 2019 04:36
lauracodecreations
/ Cronbach’s_alpha.md
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October 29, 2021 10:25
Cronbach’s alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. More information about this: https://stats.idre.ucla.edu/spss/faq/what-does-cronbachs-alpha-mean/
The code assumes that you already have uploaded your data in Azure ML, and that you have imported into Python. More information: https://gist.github.com/lauramar17/0fd5ea81be217a7ccd39cacaba7397b9.js
Method: It takes an unlimited number of parameters for the questions that you want to calculate its internal consistency.
To run: