With Kevin Potcner (Academic Ambassador, JMP)
Exploring data – especially complex multi-dimensional data – can be daunting for students new to the statistical sciences. Traditional courses that rely on formal statistical techniques and explicit use of formulas often result in exposing students only to basic analysis problems (e.g., 1-sample inference, 2-sample comparisons, analyses for only one outcome variable, etc.).
The data that these students will be presented with once they enter the workforce will not be this simple. These datasets will contain a large number of variables and not fit the simple inferential techniques that is part of the standard statistics curriculum.
The presenter will illustrate a variety of ideas on how to incorporate dynamic interactive visualization tools into your curriculum to help excite students learning the statistical sciences and better equip them to handle the types of data and problems they will face in their future jobs.
Kevin Potcner is an Academic Ambassador for JMP Statistical Discovery Software from SAS. He has 25+ years industry experience as an instructor and consultant across a wide range of industries including medical device, pharmaceutical, biotech, food & beverage, consumer goods, automotive, materials, energy, financial services, among others.
Kevin has held faculty positions at The Rochester Institute of Technology, University of Florida, University of San Francisco and is currently an instructor for California State University Data Science program. He holds an MS in Applied Statistics from The Rochester Institute of Technology.