Fifth Annual Joint Conference of the Upstate Chapters of the American Statistical Association
Canisius College, Buffalo, NY
April 22-23, 2016
The theme for this year's meeting is "Data Science, Statistical Practice, and Education." Since statistics is a major component of data science, we are soliciting abstract submissions related to the statistical analysis of data. We are interested in contributions to statistical methodology as well as to statistical practice, consulting, and education. Moreover, we would welcome submissions at the interface of statistics and other disciplines such as computer science, biology/medicine, social sciences, and business/finance. The conference will be an exciting venue for statisticians/data scientists to network and discuss topics relevant to their work and research interests.
This year, we are extremely fortunate to have Professor Richard D. De Veaux, the C. Carlisle and Margaret Tippit Professor of Statistics in the Department of Mathematics and Statistics at Williams College, as our keynote speaker. Professor De Veaux is the author of 6 textbooks and has consulted with several major corporations. He is an entertaining and engaging speaker who has made important contributions to statistics education and has interests in data mining methodology and its application to problems in science and industry. The title of his talk, to be presented in Saturday, April 23, is "From the Classroom to the Boardroom - How Do We Get There?" Professor De Veaux will also give the Fr. Haus Memorial Mathematics Lecture, "Modeling the Effect of Age in Human Performance", from 3:15pm to 4:15pm on Friday, April 22. This will be followed by a panel discussion on "The multiple facets of data science" from 4:30pm to 5:55pm, with representatives from both academia and industry.
Selected Themes For This Year's Conference
Novel contributions to statistical methods or computing
If you have developed new statistical methods or approaches to the analysis of data, we strongly encourage you to consider submitting an abstract to present your work.
Applications of statistical methods to interesting data sets from biology/medicine, social sciences, business/finance, and other fields
If you are an applied statistician working in academia or in industry, and have worked on interesting problems involving the analysis of large, complex data sets, then consider submitting an abstract to present your problem and the analysis that you performed to gain insight into your scientific question.
Issues in statistics / data science education
If you have taught courses related to statistics or data science to high school students, undergraduate students, or graduate students, consider giving a presentation on novel approaches that you may have implemented. Presentations that touch on the role that other disciplines should play in developing curricula in these fields would also be of great interest.
Statistics education in secondary schools (and beyond)
Given the vital importance of promoting statistics in education, we would especially encourage abstract submissions pertinent to statistics education in secondary schools (and beyond). Presentations could involve motivating examples of experimental design or statistical analysis derived from real-world problems; strategies for emphasizing the connections between probability and the development, evaluation, and implementation of statistical methods that are used to analyze data; ideas on how to integrate frequentist and Bayesian philosophies in a balanced curriculum; or any other innovative ideas concerning this topic.
Tutorials For This Year's Conference
The first day of the conference (Friday, April 22) will feature tutorials (1-2 hour workshops on topics of broad interest) from 9:00am to 11:00am and from 1:00pm to 3:00pm. These will include:
- "A Gentle Introduction to Statistical Learning Theory for Data Science" (Ernest Fokoue, Rochester Institute of Technology)
- "Kaggle Predictive Analytics with Random Forests and Boosted Trees" (Padraic Neville, SAS Institute)
- "An Excursion into Modern Big Data Concepts and Computational Models for Topic Discovery" (Xingchen Yu, University of California Santa Cruz)
- "Practical Natural Language Processing" (Emily Prud'hommeaux, Rochester Institute of Technology)
- "Introduction to Statistical Methods in Astronomy" (John Whelan, Rochester Institute of Technology)
Tutorials will be provided free of charge to registered conference participants. Space is limited, so reservations for a seat at a tutorial must be made here at or after the time of conference registration.
To further encourage student participation, we will hold a data analysis competition. A team of no more than 4 students may enter the competition by submitting their entry information on data competition page by Monday, February 15, 2016. The information should indicate the team name, school, and the names of the team members. The data set will be accessible from the conference website on February 15 to teams that have entered the competition. Teams will be required to submit their results and the code that they used to obtain their results by Friday, April 1, 2016. Prizes will be awarded to the top 3 teams, all of whom will be asked to present their results at the conference. Further details concerning this competition are available on the data competition page
Friday, March 11, 2016
Notification of Acceptance of Submission
Friday, March 25, 2016
Data Competition Entry Deadline
Monday, February 15, 2016
Data Competition Submission Deadline
Friday, April 1, 2016
Online Ticket Sales Close
Thursday, April 21, 2016
Thursday, April 21, 2016
Organized Session Submission Deadline
Friday, March 4, 2016
- Novel contributions to statistical methods or computing
- Applications of statistical methods to interesting data sets from biology/medicine, social sciences, business/finance, and other fields
- Issues in statistics / data science education
- Statistics education in secondary schools (and beyond)
- Other aspects of statistical methodology and applications
When and Where
2001 Main St
Buffalo, NY 14208
Cocktail Hour & Poster Session
- 9AM - 3PM: Tutorials
- 3:15 PM - 4:15 PM: Fr. Haus Memorial Mathematics Lecture
- 4:30 - 5:55 PM: Panel Discussion ("The Multiple Facets of Data Science")
- Conference: 8:00 A.M. - 5:30 P.M.
General Conference Questions