Data Analysis and Statistical Inference

Duke’s Data Analysis and Statistical Inference on Coursera is an introduction to statistics with an optional computational component using the R programming language. The course runs about 8 weeks and covers a considerable amount of ground in that time. It starts with the basics of data and data collection methods but quickly moves on to cover probability, the normal distribution, the binomial distribution, hypothesis testing, confidence intervals, Z and T statistics, ANOVA and Chi squared tests and linear regression. The course is a bit of a whirlwind tour that packs a lot into each lecture. The PDF slides that go along with the videos are a great resource to review the information dumped in each lecture. Many students complained that the course requires more time than the original estimated amount of around 6-8 hours per week. The course was later updated with an estimate of 8-10 hours per week, which is on the conservative side. If you come in with some prior knowledge of stats and R you can get through in 3-5 hours per week.

The professor is engaging and does a good job going through the material while providing adequate face time. The slides are very informative and the video quality is excellent. There are periodic in-lecture quizzes that help test your understanding of the material as you go along. I felt that the frequency of in-lecture quizzes was just about right in this course.

Great, great course. A well balanced mixture of theory, examples, labs and to learn software and projects to test your skills in the 'real' world.

The teacher explains the concepts very clearly. The course layout and order of topics is excellent. The difficulty is does not change overall. The free and open textbook is the best I've come across. It is packed with footnotes to datasets, and has more than enough examples and exercises to get you through the midterm and the exam.

The teacher is very active on the forums and even organised a Google hangout session you can join.

The focus of this course is definitely not on mathematical proofs, probability theory or working through problems analytically, but geared towards practical approaches using given formula's or R to get results on every day problems.

Integrated into the course is the datacamp environment that helps you to learn the software R by playing with data. The nature of these task mirror the theory discussed that week. There are some glitches in this new environment (during the first run of this course), and the tasks are not really challenging.

The quizzes are quite good. Many of the questions test your insight rather than ask you to do tedious algebra.

The peer reviewed research projects are time consuming, great fun and an excellent way to get your hands wet with real data, R and doing some real data analysis.

One of the best courses I've taken.

I've had plenty (cough) of time to forget the basic statistical inference I did at high school. This was a great refresher (if a little repetitive - hypothesis tests vary mainly in relatively minor-seeming details). With a little prior exposure, it's not too time consuming. But at the same time it never degenerated - in the way of much stat inf pedagogy - into a pure exercise in plugging numbers into formulae; some questions were demanding enough to require significant headscratching and envelope scribbling

And judging by the quality of the materials (video, detailed learning objectives plus references to an open textbook - more or less optional given the copious lecture material and summary "learning objectives") & reactions in the forums, it's a great introduction for people without previous exposure to the topic, with the added bonus of a gentle introduction to R (via the excellent datacamp website should you prefer).

Thanks to Dr Mine, there is now no excuse for statistical illiteracy.
No.
Ex.
Cuse.

(Update: DASI has two tracks - with and without a project and R labs. The project is supposed to be necessary for a distinction, but I just discovered that with a high enough grade on the exams/quizzes, it isn't :)