Winter School on Statistics with JMP

Author: Irena Ograjenšek, Created 2016/11/03 13:39, Last updated: 2016/11/03 13:40

The Winter School on Statistics with JMP will take place in Leuven (Belgium) from 23rd to 27th January, 2017Its aim is to provide a thorough training in statistics using the user-friendly JMP software. 

We believe that statistics training should be hands-on from start to finish, and that the explanation of theoretical concepts, demonstrations and hands-on exercises should be intertwined throughout. As we believe that the JMP software is the ideal software for exploring data, visualizing it and analyzing it statistically, we will use that software for the entire winter school. With JMP’s interactive capabilities, learning and using statistics becomes fun for applied researchers and statisticians alike. Moreover, JMP is available freely or inexpensively for academic researchers, and state of the art for the design of factorial experiments.

Prior experience with JMP is not required. 

The program for the Winter School is as follows:

Monday 23 January 2017:

8.30am     Registration and welcome

9am-5pm  Data visualization and exploration (Prof. Ellen Vandervieren, University of Antwerp)

5-5.30pm  Presentation of JMP resources for teachers (Volker Kraft, JMP)

8pm          Welcome dinner

Tuesday and Wednesday 24-25 January 2017:

8.30am     Registration and welcome

9am-5pm  Statistical inference: confidence intervals, tests and regression (Prof. David Meintrup, Ingolstadt University of Applied Sciences)

Thursday and Friday 26-27 January 2017:

8.30am     Registration and welcome

Option 1:

9am-5pm  Design and analysis of factorial experiments (Prof. Peter Goos, University of Leuven)

Option 2:

9am-5pm  Choice experiments: design and analysis (Dr. Roselinde Kessels, University of Antwerp)

Course descriptions, short bios of the teachers and online registration forms can be found here.

We hope to welcome you at the Winter School!

Peter Goos, Roselinde Kessels, David Meintrup and Ellen Vandervieren

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