The Center for Social Statistics Presents: Instructor: Daniel Lee, Columbia University Abstract: Stan is an open-source, Bayesian inference tool with interfaces in R, Python, Matlab, Julia, Stata, and the command line. Users write statistical models in a high-level statistical language. The default Bayesian inference algorithm is the no-U-turn sampler (NUTS), an auto-tuned version of Hamiltonian […]
The Center for Social Statistics Presents: Inferring and understanding travel and migration movements at a global scale Abstract: Despite extensive work on the dynamics and outcomes of large-scale migrations, timely and accurate estimates of population movements do not exist. While censuses, surveys, and observational data have been used to measure migration, estimates based on these […]
The Center for Social Statistics Presents: Mark S. Handcock (Professor, Statistics) Jeffrey B. Lewis (Professor, Political Science) Marc A. Suchard (Professor, Biomathematics, Biostatistics and Human Genetics) Abstract: Reproducibility is one of the main principles of the scientific method. This panel of scholars will discuss issues in the importance of replication of statistical results. Increasing attention […]
The Center for Social Statistics Presents: Electronic Homestyle: Tweeting Ideology Abstract: Ideal points are central to the study of political partisanship and an essential component to our understanding of legislative and electoral behavior. We employ automated text analysis on tweets from Members of Congress to estimate their ideal points using Naive Bayes classification and Support Vector […]
The Center for Social Statistics Presents: Quantifying the dynamics of multimodal communication with multimodal data Abstract: Human communication is built upon an array of signals, from body movement to word selection. The sciences of language and communication tend to study these signals individually. However, natural human communication uses all these signals together simultaneously, and in […]
The Center for Social Statistics Presents: Instructor: Michael Tzen, CCPR UCLA VIEW PODCAST HERE! PLEASE BRING A PERSONAL LAPTOP We will provide all the software tools (no installation needed) Abstract: Geographically referenced data sets are becoming increasingly common. In spatial analysis of demographic data, three common spatial indices are used: points, lines, and polygons. Through […]
The Center for Social Statistics Presents: Innovative Sampling Approaches for Hard to Reach Populations: Design of a National Probability Study of Lesbians, Gay Men, Bisexuals, and Transgender Peoples and Network Sampling of Hard to Reach Populations Speakers: Ilan H. Meyer, Williams Distinguished Senior Scholar for Public Policy at the Williams Institute Mark S. Handcock, Professor […]
The Center for Social Statistics Presents: Instructor: Michael Tzen, CCPR UCLA PLEASE BRING A PERSONAL LAPTOP Abstract: Researchers go through fundamental steps in a data analysis project. This workshop highlights key steps in a data analyst's workflow and encourages transparency in each of the steps. Throughout this workshop, we go through hands on exercises that […]