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CE_24C | Tue, 8/11/2015, 8:30 AM - 5:00 PM | S-Willow A | |
Statistical Methods for Ranking Data (ADDED FEE) — Professional Development Continuing Education Course | |||
ASA | |||
Ranking data commonly arise when ranking a set of individuals or objects in accordance with some criterion. Such data may be observed directly, or it may come from a ranking of a set of assigned scores. Alternatively, ranking data may arise when transforming continuous or discrete data in a nonparametric analysis. Examples of ranking data may be found in politics, voting and elections, market research, psychology, health economics, food tasting, and even horse racing. Many statistical methods have been developed in the recent decades for analyzing and modeling ranking data. These methods are by their nature nonparametric and consequently require no underlying assumptions on the distributions of the observed scores. In this course, participants will learn how ranking data can be analyzed for drawing inferences and how it can be modeled. Methods of handling missing data, incomplete rankings, and ties will be introduced. Most of these methods will be illustrated by application to real data sets. We will have computer demonstration of using a number of R packages, including StatMethRank, a companion R package to our book titled Statistical Methods for Ranking Data, Springer. | |||
Instructor(s): Mayer Alvo, University of Ottawa, Philip L.H. Yu, The University of Hong Kong |
For program information, contact the JSM Registration Department or phone (888) 231-3473.
For Professional Development information, contact the Education Department.
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