Full course description
Term: Fall 2021
Date: August 27, 2021 & September 17, 2021 (2-day workshop)
Time: 12:00pm - 1:00pm both days
Location: ONLINE ONLY
Instructors: Jennifer Van Mullekom, Frances McCarty, & Kate Miller
Presented By: Statistical Applications & Innovations Group (SAIG)
The data available for analysis across all disciplines – science, engineering, and business – is growing at an extraordinary rate. It is expected that today’s professionals across academic and industry disciplines have a much higher level of data analysis proficiency that years past. Programming environments such as R and Python, though extremely valuable for many applications, are often not the best tool for analyzing data quickly following a natural data exploration workflow.
In this session, Kevin Potcner – a statistical scientist from JMP – will illustrate a variety of data visualization techniques and statistical analysis tools in JMP that can greatly enhance the speed at which you are able to explore data to extract the key insights and features. Teachers will see examples of how analyzing data in an interactive software environment quickly brings the data to life and can excite students in learning the statistical sciences. Students will be exposed to tools that they will be expected to have experience with as they begin their professional careers, and researchers will see how quickly they can run formal statistical analyses to test their research hypotheses. Topics covered will include: Graphing and data visualization, One- and two-sample inferential statistics, Sample size determination, Linear Models (ANOVA, Regression), Design of Experiments, Analysis of multivariate data, Predictive Modeling.