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Hoboken, NJ: Wiley 978-1119002253.
McKinney, W. (2017). Python for data analysis: Data wrangling with Pandas, NumPy and IPython
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14 Data
HHS. (2003). HIPAA privacy rule for research. Retrieved April 24, 2018, from https://www.
hhs.gov/sites/default/files/ocr/privacy/hipaa/understanding/special/research/research.
pdf?language=es.
HHS. (2012). Guidance regarding methods for de-identification of protected health information
in accordance with the Health Insurance Portability and Accountability Act (HIPAA) Privacy
Rule, November 26, 2012. Retrieved May 1, 2018, from https://www.hhs.gov/sites/default/files/
ocr/privacy/hipaa/understanding/coveredentities/De-identification/hhs_deid_guidance.pdf.
ICPSR. (2018). Recommended informed consent language for data sharing. Institute for Social
Research at the University of Michigan. Retrieved May 1, 2018, from https://www.icpsr.umich.
edu/icpsrweb/content/datamanagement/confidentiality/conf-language.html.
Knaflic, C. N. Storytelling with data: A data visualization guide for business professionals.
Hoboken, NJ: Wiley 978-1119002253.
McKinney, W. (2017). Python for data analysis: Data wrangling with Pandas, NumPy and IPython
(2nd ed.). Newton, MA: O’Reilly Media 978-1491957660 (or current edition).
O’Neil, C., & Schutt, R. (2013). Doing data science: Straight talk from the frontline. Newton, MA:
O’Reilly Media 978-1449358655.
Press, G. (2013, May 28). A very short history of data science. Forbes. Retrieved December
4, 2018, from https://www.forbes.com/sites/gilpress/2013/05/28/a-very-short-history-ofdata-science/#2fbb886355cf.
Retrieved May 1, 2018, from http://www.wpuda.org/assets/Energydocs/model%20data%20privacy%20guideline%20for%20large%20utilities%2009%2008%2016.pdf.
Richards, N. M., & King, J. H. (2014). Big data ethics. Wake Forest Law Review, 49, 393.
State of Washington. (n.d.). Data privacy guidelines for large utilities. Washington, DC: State of
Washington.
Towards Data Science. (n.d.). Retrieved December 4, 2018, from https://towardsdatascience.com/.
14 Data