Some familiarity with the R statistical programming language (http://www.r-project.org/) and proficiency in writing in English will be useful. At Johns Hopkins, this course is taken by first-year graduate students in Biostatistics.
The course will consist of lecture videos broken into 8-10 minute segments. There will be two major data analysis projects that will be peer-graded with instructor quality control. Course grades will be determined by the data analyses, peer reviews, and bonus points for answering questions on the course message board.
This course will focus on how to plan, carry out, and communicate analyses of real data sets. While we will cover the basics of how to use R to implement these analyses, the course will not cover specific programming skills. Computing for Data Analysiswill cover some statistical programming topics that will be useful for this class, but it is not a prerequisite for the course.
A computer with internet access on which the R software environment can be installed (recent Mac, Windows, or Linux computers are sufficient).
There is no standard textbook for data analysis. The course lectures will include pointers to free resources about specific statistical methods, data sources, and other tools for data analysis.