In this course(R Programming), you will learn how to program in R and use it for effective data analysis. You will learn how to install and configure software that is necessary to run for a high-level statistical programming environment. This course covers all the important concepts in statistical computing. It includes programming in R such as reading the data, accessing packages in data analyst, writing function, profiling the codes, and organizing. Also, cover topics in statistical data analysis that will provide your working area.
- This week covers the basics of R Programming. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 covers the history of R, goes over the basic data types in R, and describes the functions for reading and writing data.
- 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.
- We 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 languages make R programming useful for both interactive work and writing longer code.
- This week 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. A profiler is a key tool in helping you to optimize your programs. Finally, we cover the str-function, which I personally believe is the most useful function in R.