Key Information
About the content
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.
Syllabus
- Week 1 - Week 1: Background, Getting Started, and Nuts & Bolts
This week 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 descri... - Week 2 - 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. - Week 3 - Week 3: Loop Functions and Debugging
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 of R make R useful for both interactive work and writing longer code, and so they a... - Week 4 - Week 4: Simulation & Profiling
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 addresse...
Instructors
Roger D. Peng, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health
Jeff Leek, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health
Brian Caffo, PhD
Professor, Biostatistics
Bloomberg School of Public Health
Content Designer
Johns Hopkins University (JHU) is a private American university located in Baltimore, Maryland. It also has campuses in Washington, D.C. Bologna, Italy, Singapore and Nanjing, China. It owes its name to Johns Hopkins, a wealthy entrepreneur who bequeathed 7 million dollars to the university on his death.
One of the most prestigious universities in the United States (especially for its faculties of medicine and public health, as well as its school of international affairs), the institution defines itself as the country's leading "research university". At the beginning of its history, it was mainly inspired by the University of Heidelberg and the German educational model of Wilhelm von Humboldt. In 2019, 39 Nobel Prize winners have their names associated with the university.
Platform
Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California.
Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.
This course will teach you a lot but it is very difficult. The programming assignments are very challenging. I would not recommend this for someone who has never used R before.
In this course, a tutor should explain what is rnorm and how their values are distributed and also assignments are way much harder for beginners. we cannot even have an idea how the particular function should be created.
good course, But I would like to see something approaching codding more like production, or even projects, real life projects to in.
This course will teach you a lot but it is very difficult. The programming assignments are very challenging. I would not recommend this for someone who has never used R before.
Its really well concieved. I didn't have to have past experience in statistics to learn R, yet since I do have some background, it was fun to mess around with it.I learned enough to get me started with R. Thank you very much.
Though I have learned R for 5 years, I still found some very interesting contents and insight opinion, by the way, all the mentors of this course are very professional and accommodating.
