Learn how to create lightweight, interactive data visualization apps for medium-sized datasets. This will be useful for introducing students and researchers to basic exploratory data analysis. We will begin with a basic introduction to data frames in Python and R using a basic dataset; then we will see how to render that data as an interactive dashboard in Python and R; finally, we will deploy see what deploying your app to a free public web server in Heroku looks like!
Have you ever wanted to learn how to use R to make estimates about your dataset? Come to this session prepared to learn about the basics of multiple linear regression, and use an interactive demo website where you can upload your own data as a CSV file and learn how to make predictions with it. We will have a sample CSV file prepared for you, or bring your own.
Did you know that the popular R data visualization library ggplot was created by a Rice professor? Come take this course to learn all about the power of R and ggplot, including plot styles, aesthetic mappings, geometric objects, and statistical transformations.
In this short course, we will go over some strategies for importing, reshaping, accessing and visualizing data! Take this course if you are interested in improving your statistical analysis skills in R. Beginners should take Introduction to R before taking this course.
Come learn the basics of R Statistical Programming Language, a powerful tool for statistical analysis, visualization, modeling and more! In this beginner-friendly class, you will learn some basic data types and commands to get you up and running inside RStudio.