This class is an intensive introduction to R. It starts with the very basics of assigning variables and reading data. It then progresses to using RMarkdown for document and presentation creation.
DurationThis class is an intensive introduction to R. It starts with the very basics of assigning variables and reading data. It then progresses to using RMarkdown for document and presentation creation.
University Mission Statement
Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields.
The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis.
It seeks to attract a diverse and international faculty, staff, and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the University to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.
Data science is huge, and the ability to tackle analysis problems in a highly specialized and fast language will help people who are not engineers approach the topic.
Statistical computing is employed within a diverse range of industries. In recent years, an open source project, R, has emerged as the preeminent statistical computing platform. With its unsurpassed library of freely available packages, R is capable of addressing almost every statistical inference ...
This course is a 35-hour program designed to provide a comprehensive introduction to R. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data.
In this course, you’ll use advanced modeling techniques to predict, classify and group data. You’ll use more advanced techniques to help you understand both inferential and predictive approaches.
The R Programming Introduction course will help students learn how to perform data analysis with the R language and software environment, even if they have little to no programming experience.
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