10_data_theory.rmd

# (PART) Data {-} 

# Data Theory {#datatheory}





## Introduction

"The plural of anecdote is data." -- Raymond Wolfinger, 1969-70

* see [The plural of anecdote is data, after all](http://blog.revolutionanalytics.com/2011/04/the-plural-of-anecdote-is-data-after-all.html)



What is data science without _data_?  


## Understand your data

Randy Au, 2019-02-15, [Know your data. Really, really, know it](https://towardsdatascience.com/data-science-foundations-know-your-data-really-really-know-it-a6bb97eb991c)


## Bias

Harini Suresh and John V. Guttag, [A Framework for Understanding Unintended Consequences of Machine Learning](https://arxiv.org/abs/1901.10002), arXiv:1901.10002v1  [cs.LG]  28 Jan 2019


Tim Harford (2019-03-08) [Black holes in data affect health and wealth](http://timharford.com/2019/04/black-holes-in-data-affect-health-and-wealth/), blogpost at timharford.com


Cathy O'Neil (2016) _Weapons of Math Destruction_ [@ONeil_2016]


Caroline Criado Perez (2019) _Invisible Women_ [@Perez_2019]
 
* Lulu Garcia-Navarro, [interview with Caroline Criado Perez](https://www.npr.org/2019/03/17/704209639/caroline-criado-perez-on-data-bias-and-invisible-women), 2019-03-17

* Angela Chen (2019-03-05) [A journalist explains the dangerous consequences of a world built for men](https://www.theverge.com/2019/3/5/18251570/caroline-criado-perez-invisible-women-data-bias-science-gender), [theverge.com]


 ***