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Exploratory, Inferential and Predictive data analysis. Feel free to show your :heart: by giving a star :star:

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# Readme
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The one common issue which novice entrants in data science have always asked me is, "How to begin their data analysis journey?".
My answer has always been the same, "Tell a data powered story!". But, one will be in a position to tell a "story" only if he/she knows the *nuts and bolts* of the story. If you are a *novice* in statistics or applied mathematics, I recommend to check out the `resources` folder, first.

The repository contains `data`, `code`, `resources` and `plots` folders.

###### Have a question?

Ask your question on [Stack Overflow](http://stackoverflow.com/questions/tagged/r)
or the [R-SIG-Finance](https://stat.ethz.ch/mailman/listinfo/r-sig-finance)
mailing list (you must subscribe to post).

## Contributing [![contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/duttashi/learnr/issues)

Please see the [contributing guide](CONTRIBUTING.md).

## Author
[Ashish Dutt](https://duttashi.github.io/about/)

learnr

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