SAS + R Part 1: Connecting SAS and R in Your Data Science Workflow
Presented: April 26, 2021, 10:00am-2:00pm Pacific Daylight Time
Hunter Glanz is an Associate Professor of Statistics and Data Science at California Polytechnic State University (Cal Poly, San Luis Obispo). He received a BS in Mathematics and a BS in Statistics from Cal Poly, San Luis Obispo followed by an MA and PhD in Statistics from Boston University. He maintains a passion for machine learning and statistical computing, and enjoys advancing education efforts in these areas. In particular, Cal Poly’s courses in R, SAS, and Python give him the opportunity to connect students with exciting data science topics amidst a firm grounding in communication of statistical ideas. Hunter serves on numerous committees and organizations dedicated to delivering cutting edge statistical and data science content to students and professionals alike. In particular, the ASA’s DataFest event at UCLA has been an extremely rewarding experience for the teams of Cal Poly students Hunter has had the pleasure of advising.
As robust statistical software packages, SAS and R boast a great number of tools for addressing all of your data-related needs. While there exists large overlap in what they provide, today’s statistical and data science problems increasingly involve multiple software packages. After all, if you have access to all of these tools then why not explore how they can improve your workflow! In this class we will explore the complete workflow of cleaning a dataset, exploring it, visualizing it using a combination of SAS and R.