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Are you uncomfortable applying statistics to your data in a way other people (or even worse, tools) dictate?
Learn first why much of what is being done is actually incorrect, and then how to do it right.

Date: February 2, 2016, 08:45am –12:30pm

Location: HCI G 7

Program:
08:45-09:30  Statistics debunked: why normal is incorrect
09:45-12:30  Statistics revamped: what you should do, and why

The course will cover the following topics:

  • Probability Distribution, Cumulative Distribution
  • Robustness of Statistics
  • Student-t and Chi Square (and why not to use them)
  • Binomial Distribution Method (robust, distribution independent)
  • How to report data
  • Quantized Data (Questionnaires, Marks ...)
  • Slopes and Bootstrapping
  • Probability Theory - The Logic of Science (Bayes Formula)
  • Comparing Groups by Bootstrapping
  • Maximizing Entropy, Mean, and Median
  • Kernel Density Estimation

Speaker: Prof. Dr. Hanspeter Schmid
Institute of Microelectronics, University of Applied Sciences and Arts, Northwestern Switzerland FHNW

Prof. Hanspeter Schmid received the diploma in electrical engineering in 1994, the post-graduate degree in information technologies in 1999, and the degree Doctor of Technical Sciences in 2000, all from the Swiss Federal Institute of Technology (ETH Zürich), Switzerland. He joined the Institute of Microelectronics of the University of Applied Sciences Northwestern Switzerland (IME/FHNW) as a research fellow in 2005 and became a full professor in February 2012. He is also a part-time senior lecturer at ETH Zürich (Analog Signal Processing and Filtering).

In order to get printed handouts please register at http://goo.gl/WH3nif

Events can be easily imported via Events in our website.

Download the Statistics in Science poster here (PDF).