Programming in R
- To equip students with knowledge how to program in R and how to use R for effective data analysis.
- Install and configure the software required for the statistical programming environment
- Configure statistical programming software
- Understanding how to use R for efficient data analysis;
- Understand critical programming language concepts
- Should make use of R loop functions and debugging tools
- Collect detailed information using R profiler
- Background, Getting Started, and Nuts & BoltsThis unit covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story
- Programming with RWelcome to Unit 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.
- Loop Functions and DebuggingWe have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they are commonly used in practice
- Simulation & ProfilingThis unit covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addressed. The profiler is a key tool in helping you optimize your programs. Finally, we cover the str function, which I personally believe is the most useful function in R III
- Экзамен в формате тестаIt is organized online via Coursera platform (final test for the course) or via LMS systems with questions related to the content of the course. Students get information about online platform not later than 3 days before exam.
- Online course attendance
- Interim assessment (4 module)0.4 * Online course attendance + 0.6 * Экзамен в формате теста
- Medeiros, K. (2018). R Programming Fundamentals : Deal with Data Using Various Modeling Techniques. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1904978
- Ren, K. (2016). Learning R Programming. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1409189
- Trejo, O., & C. Figliozzi, P. (2017). R Programming By Example : Practical, Hands-on Projects to Help You Get Started with R. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1682395