In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
Control Structures - If-else
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Habilidades que você aprenderá
Data Analysis, Debugging, R Programming, Rstudio
Avaliações
WH
Feb 03, 2016
"R Programming" forces you to dive in deep.\n\nThese skills serve as a strong basis for the rest of the data science specialization.\n\nMaterial is in depth, but presented clearly. Highly recommended!
AK
May 27, 2017
This was very engaging, however, the level of expectation and effort needed is much greater than course 1 - ToolBox.\n\nThis is perhaps the best course on R Programming designed for a small duration.
Na lição
Week 2: Programming with R
Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.
Ministrado por
Roger D. Peng, PhD
Associate Professor, Biostatistics
Jeff Leek, PhD
Associate Professor, Biostatistics
Brian Caffo, PhD
Professor, Biostatistics
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