R for Scientists
What you'll learn
- How to write R code in scripts and functions
- Obtain summary statistics, aggregate data, and create statistical models
- How to work with data: load, transform, aggregate, and graph
- Basic brogramming concepts like data structures and loops
- Familiarity with basic statistics
So you need to learn R, but you've never programmed before. Don't panic! In this course, we'll take you on a guided tour of how to code and do data analysis in base R. You'll learn to load data, summarize it, analyze it, model it, and visualize it. You'll learn about thorny real-world issues, like handling missing values and loading mis-formatted data files.
We'll cover the fundamentals of programming. We'll talk about key programming concepts, like data structures and the flow of control. And you'll practice writing code as we go, tackling problems that progressively challenge you and build your confidence, on carefully crafted example data sets.
I won't take shortcuts, gloss over details, or just give you easy cut-and-paste examples. I want you to walk away from this class as a junior programmer in R, able to approach whatever real data problems you face at work, in school, or in your research. I've worked in R almost every day for over a decade, in research and industry, to solve real data problems -- and I want to help you do the same.
This course is appropriate for someone with no programming experience. High-school level statistics, and a familiarity with tabular data (like in Excel) is helpful.
It addresses base R. It does not cover the Tidyverse collection of libraries.
Who this course is for:
- Researchers and academics with limited programming experience
- R users who want a more formal introduction to the language
- Analysts who want to add another tool to their skillset
- People planning a switch into a data science career
- Graduate students in the sciences
Jasper McChesney is a data professional, with over a dozen years' experience working in analytics, visualization, and information design -- in domains spanning biological science to human resources, to digital advocacy. His data. visualization work has won awards and been featured by various news outlets.
He is also a semi-regular instructor, and has taught introductory programming to students from a wide range of backgrounds (sometimes with LEGO robots). He has a formal training in both the life sciences and the humanities, and enjoys teaching those who don't come from a technical background.
Mr. McChesney's teaching philosophy is to emphasize learning by doing, the repetition of key concepts, and scaffolding new knowledge on old. His lectures are casual, and he avoids talking down to his audience. Past students have said:
"He has a very effective explanation style. I've taken similar classes in the past but never understood as much as I do in this class."
"Jasper was very understanding and kind. He really wanted us to learn R and be able to use it effectively."
"Jasper is an excellent lecturer. His assignments were not exhausting nor impossible. He really has a talent for designing homework problems."
Jasper McChesney currently works as a senior data analyst for a major public university.