SAS Institute provides analysis software for research and teaching purposes at universities worldwide. Our software supports many topics in teaching at higher education institutions.
Join us for an afternoon of inspirational presentations of SAS® Analytics on February 22nd from 12:30 to 17:00, Radisson Blu Saga Hotel.
SAS Analytics provides an integrated environment for predictive and descriptive modeling, data mining, text analytics, forecasting, optimization, simulation, experimental design and more.
In the audience are teachers and researchers from the University of Iceland, the Agricultural University of Iceland and Reykjavik University together with the SAS User Group in Iceland.
Please register by e-mailing Ane Gerken at ane.gerken@sas.com
Program:
Introduction to SAS Institute and SAS in Iceland
Magnus Gudmundsson, SAS Institute partner in Iceland.
SAS Academic. Supports teaching, learning and research in education
Hear how SAS Academic gives you a number of services that support the use of SAS software in teaching and research. Ane Gerken, Academic Consultant, SAS Institute.
Experience of using SAS for teaching statistics
The Agricutural University of Iceland has been using SAS software for courses in statistics since 2007. Hear how they benefit using SAS software in their teaching. Gudni Torvaldsson, professor, the Agricultural University of Iceland, Erla Sturludottir, teaching assistant, the Agricultural University of Iceland.
Break
Hierarchical linear models and repeated measures in SAS
A short course on hierarchical linear models for clustered data and repeated measures of continuous outcomes using SAS. Repeated measures and random effects approaches to model definitions using PROC MIXED will be discussed and the choice of covariance structure. Extensions to repeated measures of categorical data will be shown via generalized linear mixed models with examples from PROC GLIMMIX. Thor Aspelund, Associate Professor, University of Iceland.
Break
Beyond hypothesis testing
Following a long historical tradition scientists have been using statistical hypothesis testing as the golden standard of getting knowledge out of data. There is no doubt that hypothesis testing will stay on as an important approach many years to come, but the extraordinary development within information technology the last 40 years has illuminated certain short comings of hypothesis testing and fueled interests in alternative approaches such as explorative methods, data mining, machine learning, knowledge discovery in databases, etc. In this presentation we take a look at the differences between the approaches, pros and cons, and dive in to some examples of how to go about them using SAS software. Kaare Brandt Petersen, Project Manager, Analytics, Ph.D., SAS Institute.
Wine and chats
