Visualizing Your Data: Graphical Programming in R
Course enrollment will be available for this course once it is scheduled.
We will use the statistical programming language R to graphically represent data. Students will be able to present their data in a compelling way. This will be useful for many fast-growing fields of study including public health and biomedical sciences.
Advances in computing power have enabled scientists to amass huge amounts of data on everything from genetics to climate science, but there is a need for someone to make sense of this data. In this class we will learn how to perform basic statistical analysis and visualize data using the statistical software R. Motivating examples will include using epigenetic data such as DNA methylation to predict cancer status, and mapping heat waves across the country. These tools will prepare students for a variety of fields in college, including public health, statistics, economics, and biology. R is a good introductory programming language with excellent graphical capabilities, and can easily be picked up by someone who has no experience programming.
By the end of the course, student's will have learned how to read data sets into R, run basic analyses such as finding the mean and standard deviation of data and running simple linear models, make plots such as histograms, pie charts, boxplots, scatterplots, and heatmaps.
Algebra I is preferred.