Jeremy Entner, Ph.D., joined Cornell’s Department of Statistics and Data Science as a Lecturer in 2019, where he teaches several courses including “Biological Statistics,” “The Theory of Interest,” and “Statistics for Risk Modeling.” He previously spent six years at the University of Tennessee at Martin teaching courses on mathematics and statistics. Dr. Entner holds a B.S. and M.A. in Mathematics from SUNY Brockport. He earned his Ph.D. in Mathematics with an Emphasis on Statistics from Syracuse University.
When you think about what data analysts and data scientists do on a day-to-day basis, you might have a general understanding of types of conclusions they make, but how do they arrive at those conclusions? The statistical programming language R is widely used in data science; understanding the basics of how it works can help you manipulate and visualize data in a quick, flexible manner, and it may improve your communication with data scientists on your team.
In this course, you will explore the basics of statistical programming and develop R skills. As you hone your ability to use commands in R, you will combine those basic skills to complete more complex tasks, such as data manipulation and visualization. Finally, you will examine how to repeat tasks in R, which makes it easier to manipulate large data sets. This course involves many hands-on coding exercises to help you gain confidence in your newfound programming skills.
System requirements: This course contains a virtual programming environment that does not support the use of Safari, Edge, tablets, or mobile devices. Please use Chrome, Firefox, or Internet Explorer on a computer for this course.
Key Course Takeaways
- Perform basic mathematical operations, create sets of data, and use built-in R functions
- Bring data into your RStudio workspace and modify it
- Visualize data by making customizable plots
- Use code to repeat processes and select samples from your data
How It Works
Who Should Enroll
- Current and aspiring data scientists and analysts
- Business decision makers
- Marketing analysts
- Anyone seeking to gain deeper exposure to data science