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.
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About this Course
Familiarity with regression is recommended.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
Understand critical programming language concepts
Configure statistical programming software
Make use of R loop functions and debugging tools
Collect detailed information using R profiler
Skills you will gain
- Data Analysis
- Debugging
- R Programming
- Rstudio
Familiarity with regression is recommended.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Week 1: Background, Getting Started, and Nuts & Bolts
Week 2: Programming with R
Week 3: Loop Functions and Debugging
Week 4: Simulation & Profiling
Reviews
- 5 stars68.12%
- 4 stars22.14%
- 3 stars5.83%
- 2 stars2.06%
- 1 star1.83%
TOP REVIEWS FROM R PROGRAMMING
This is a very thorough introduction to R. There are plenty of exercises to quickly get familiar with the language. Some good guided assignments really help getting familiar with coding functions.
Nice course but it would be better if more links to this course and exercises were added for students to be able to have more practices not only with swirl ( ) but also with trustable third parties.
I would have preferred the 'robot voice' concept from the toolbox course, since it could be updated to more recent R upgrades, but the assignments really made me think and that was my favorite part.
Very challenging, but good course. I've been programming in R for over a year, but there were still some things for me to pick up in this class. Assignments were a challenge, but satisfying to tackle.
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