Data Analysis @ John Hopkins University
This course is an applied statistics course focusing on data analysis. The course will begin with an overview of how to organize, perform, and write-up data analyses. Then we will cover some of the most popular and widely used statistical methods like linear regression, principal components analysis, cross-validation, and p-values. Instead of focusing on mathematical details, the lectures will be designed to help you apply these techniques to real data using the R statistical programming language, interpret the results, and diagnose potential problems in your analysis. You will also have the opportunity to critique and assist your fellow classmates with their data analyses.
Start Date: 22nd of January 2013 (8 weeks long)
Workload: 3-5 hours a week
How it works
The Data Analysis course is available through the learning platform provided by Coursera. Additionaly to this, we are starting a study group here in Graz – to learn together and meet other interested people.
The online 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.
The study group here in Graz will meet once a week to learn together. Spektral with their Free University project offers the infrastructure for the learning sessions, but it’s not obligatory to use it. This all will be organized by us via the mailinglist and doodles week by week, so just subscribe to the mailinglist for more informations.
- Subscribe to the Mailinglist and you will get all information
- Enroll to the Data Analysis Course on Coursera
- Join the Open Science Course, if you are interested in doing it the open way
The course, as the study group, will be held in English, so also international students are very welcome.
Open Science Partnership
The study group is made in cooperation with the Open Science Project, so the whole exercises and experiences will be documented and done in a free and open way. Interested in doing it the open science way? Then look at their page for this course and join them.