Signal and Noise: an Introduction to Statistics
247 West 37th St, 5th Floor
New York, NY 10018
How do numbers relate to the world? What insights can we derive from data? How do we separate signal from noise? This course is an introduction to statistical thinking and its applications to data analysis at a level accessible to a broad audience with no prior statistical background. We’ll learn and make intuitive the fundamental methods and concepts of data quantification: p values, margins of error, linear regression, logistic regression, probability distribution, hypothesis testing, statistical significance, and correlation vs. causation. We’ll examine, too, the role of data in the world—its omnipresence and utility for science, business, technology, and public policy. In what sense are we data-driven? Why do predictive models work and yet sometimes, unexpectedly, err? In what ways can statistical techniques be used, intentionally or not, to wildly mislead and convincingly support falsehoods and biases? In this course, we’ll not only learn fundamental statistical methods, but also examine the limitations of data, its predictive capacities, and its uses and abuses.
Course ScheduleTuesday, 6:30-9:30pm
June 05 — June 26, 2018