Chapter 6 Data Theory
6.1 Introduction
“The plural of anecdote is data.” – Raymond Wolfinger, 1969-70
What is data science without data?
6.2 Understand your data
Randy Au, 2019-02-15, Know your data. Really, really, know it
6.3 Bias
Harini Suresh and John V. Guttag, A Framework for Understanding Unintended Consequences of Machine Learning, arXiv:1901.10002v1 [cs.LG] 28 Jan 2019
Tim Harford (2019-03-08) Black holes in data affect health and wealth, blogpost at timharford.com
Cathy O’Neil (2016) Weapons of Math Destruction (O’Neil 2016)
Caroline Criado Perez (2019) Invisible Women (Perez 2019)
Lulu Garcia-Navarro, interview with Caroline Criado Perez, 2019-03-17
Angela Chen (2019-03-05) A journalist explains the dangerous consequences of a world built for men, [theverge.com]
References
O’Neil, Cathy. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown.
Perez, Caroline Criado. 2019. Invisible Women: Data Bias in a World Designed for Men. Harry N. Abrams.