Introduction to Statistical Programming in R
Course
In Providence (USA)
Description
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Type
Course
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Location
Providence (USA)
Course Information
Course Code: CECS0908
Length: 2 weeks
Program Information
Summer@Brown
Brown’s Pre-College Program in the liberal arts and sciences, offering over 200 non-credit courses, one- to four-weeks long, taught on Brown’s campus. For students completing grades 9-12 by June 2020.
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Subjects
- Programming
- Statistics
Course programme
Course Description
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.
*Students are highly encouraged to bring their own laptops to campus if they plan on enrolling in this class. The course work will be heavily dependent on having access to a laptop. For those students who do not have one, there may be loaners available through our Computer and Information Technology center. Laptop loaners are provided on a "first come, first served" basis.
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: Algebra I is preferred.
Introduction to Statistical Programming in R