The last Economics Colloquium of the year, at 4:30 on Wednesday, May 27th, Steitz 102:
Data Science for Humans
Shilad W. Sen Macalester College,Associate Professor, Mathematics and Computer Science
Data scientists mine massive datasets to help software understand our tastes, needs, and routines. Want to become a data scientist? Many new data science degrees incorporate coursework in statistics and computation. However, most programs focus shallowly on data, without deeply connecting to existing domain knowledge in the fields in the social science, humanities, marketing, etc. Continue reading Data Science for Humans
UPDATE: Schafer tapped to lead Large Synoptic Survey Telescope(LSST) Informatics and Statistics Science Collaboration.
Big Science + Big Data = Big Opportunities: An Overview of Statistics in Astronomy
Department of Statistics
Carnegie Mellon University
Progress in disciplines such as astronomy is increasingly being made through large-scale, multi-institution projects, often referred to as “Big Science.” It is only through careful statistical analysis that the massive amount of information (the “Big Data”) produced by these endeavors will be translated into answers to the questions of interest. This talk will make a connection between fundamental statistical concepts and the challenges facing astronomers and cosmologists as they seek to make use of the flood of data that result from modern experiments.
Monday, May 18, 4:30 p.m.
Steitz Hall 102
Tyler Vigen has opened up the world of spurious correlations like no other with his aptly titled website, Spurious Correlation. Whether it’s the remarkably tight relationship between US spending on science, space and technology with suicides by hanging, strangulation and suffocation or a more loosely related relationship between Stanley Cup goals and Suicide by Pesticide (I made that one up myself!), Vigen is Johnny-on-the-Spot with fitting data for no greater purpose than amusement.
Via Kottke, of course.
Scraping Data and Making “Big” Inferences
Arnold F. Shober
Abstract: “Big Data” does little to explain the human condition, but it offers unprecedented opportunities to model how people choose. Professor Shober will describe how Google and Amazon know what you want with uncanny accuracy, and how in his research program he uses similar tools to examine how journalists cover politicians. He will also discuss some of the practical and statistical difficulties when analyzing billions of data points.
The talk is March 6 at 11:10 a.m. in Steitz Hall 102.
UPDATE: A very good talk. Unfortunately, we did not get video for his one.