Lectures
Below you’ll find a list of links to lecture notes and code, along with the lab session materials and additional reference materials.
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Introduction to Course, R and RMarkdown (9/3)
[lecture slides]
Lecture Materials:
Recommended Readings:
- Introduction to R for Data Science (chapters 1,4,5)
- Happy Git with R (chapter 12)
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Introduction to Git, GitHub, and homework submission (9/5)
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Basic R, data types and vectors (9/10)
R files: If you have the course repository set up, you should already have them on your laptop.
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Basic R, data types and vectors
R files: If you have the course repository set up, they should already have them on your laptop.
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Vectors and sorting
R files: If you have the course repository set up, they should already have them on your laptop. Go to the directory of our course repository on your local folder and click on the .Rproj file to open the directory.
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Vector arithmetic, indexing, and basic data wrangling
R files: If you have the course repository set up, they should already have them on your laptop. Go to the directory of our course repository on your local folder and click on the .Rproj file to open the directory.