Math 118: Introduction to Data Science

Intro to data science and statistical thinking. Learn to explore, visualize,and analyze data to understand natural phenomena, investigate patterns, model outcomes,and make predictions, and do so in a reproducible and shareable manner. Gain experience in data wrangling and munging, exploratory data analysis, predictive modeling, data visualization, and effectively communicating results. Work on problems and case studies inspired by and based on real-world questions and data. The course will introduce and focus on the R statistical computing language.


Course info

Lectures

  Warner 100      MWF 1:45-2:35PM Eastern

Teaching team and office hours
Professor Becky Tang   M 3:00-5:00pm; F 10:30am-12:00pm; by appointment
TA Evan Hunter Su 7:00-9:00pm WNS 010

Texts

All books are freely available online. Hardcopies are also available for purchase.
R for Data Science Grolemund, Wickham O'Reilly, 1st edition, 2016
OpenIntro Statistics Diez, Barr, Çetinkaya-Rundel CreateSpace, 4th Edition, 2019
Introductory Statistics with Randomization and Simulation Diez, Barr, Çetinkaya-Rundel CreateSpace, 1st Edition, 2014

Materials

You should have a fully-charged laptop, tablet with keyboard, or comparable device to every lecture and lab session.





Syllabus

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