Conference Details
The Statistics Department will be hosting an Introductory Data Analytics Workshop on Saturday, April 4, 2015. To register, contact Cheryl Smalley at [email protected]
The workshop is designed for those interested in learning how to organize data and perform widely-used statistical methods.
No experience required! This is a great opportunity to learn how to use data analytics in your teaching or scholarship.
Purpose of the Workshop
The world of "big data" is dramatically impacting the way researchers explore systems and examine hypotheses. The amount of data (or information) in our world has been exploding, and analyzing these large data sets will become even more critical. Every sector of the economy will have to grapple with the implications of big data.
Data analysis is the process of finding the right data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results. The purpose of this workshop is to provide a brief overview of how to organize data and perform some of the most widely-used statistical methods using the R statistical programming language.
This workshop will be a hands-on guided exploration, and the participants will have the opportunity to reinforce the material discussed by performing analysis in R.
This workshop will not assume that participants have prior experience with R.
April 4, 2015
Mary Idema Pew Library, Computer Lab 001
- Session 1: 9:00 am – noon Getting Started Analyzing Data in R
- Introduction to R, R Studio, and Data Structure
- Basic Statistical Methods
- Data Cleaning and Manipulation
- Complimentary Lunch: noon – 1:00 p.m., Mary Idema Pew Library, Multi-Purpose Room
- Session 2: 1:00 p.m. – 3:30 p.m. Predictive Modeling and Visualization in R
- Predictive Modeling
- More Advanced Visualization
In addition to the complimentary lunch, we plan to take a break mid-morning and mid-afternoon.
Facilitators: John Gabrosek, Laura Kapitula, Paul Stephenson and David Zeitler
Registration: Contact Cheryl Smalley at [email protected] if you have interest in securing a spot for the Data Analytics Workshop on April 4.