Course Dates | Length | Meeting Times | Status | Format | Instructor(s) | CRN |
---|---|---|---|---|---|---|
July 19, 2021 - August 11, 20217/19 - 8/11 | 3 Weeks | Online | Open | Online | Melissa Eliot Kyle Gerst Alexander Sokolovsky | 11826 |
July 19, 2021 - August 11, 20217/19 - 8/11 | 3 Weeks | Online | Open | Online | Melissa Eliot Kyle Gerst Alexander Sokolovsky | 11825 |
July 19, 2021 - August 11, 20217/19 - 8/11 | 3 Weeks | Online | Open | Online | Melissa Eliot Kyle Gerst Alexander Sokolovsky | 11824 |
We will use the statistical programming language R to solve problems and analyze and graphically represent data. R is a popular programming language for statistics and data mining, and is a great first language to learn.
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 coloring maps in the world by various attributes, making sense of DNA data, and analyzing the stock market. 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 and perform simple analyses on data sets, write their own loops, and make plots to visualize their data such as histograms, pie charts, boxplots, scatterplots, and maps. This will prepare students for college-level statistics and programming classes.
Prerequisites: None, Algebra 1 recommended
Summer@Brown
Brown’s Pre-College Program in the liberal arts and sciences for students completing grades 9-12 by June 2021.
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