PhD+ Data Literacy: Exploratory Data Analysis

While many researchers want to jump right into developing statistical models and making predictions on their data, it important to first be able to understand the data. The process of initially understanding your data is called exploratory data analysis or EDA. EDA involves investigating your data using various methods, including graphical and numerical. This session will introduce the dplyr and ggplot packages as tools that will allow users to look for initial patterns in their data, check for missing data, and to set themselves up to move forward with statistical analysis.

Instructor

David Martin - Clinical Research Data Specialist

For workshop materials, please visit https://uvastatlab.github.io/phdplus2020/.

Graduate students register here

Postdocs register here