UT.7.01x: Foundations of Data Analysis is a gentle, 13 week introduction to statistics and the R programming language provided by the UT Austin through the edX MOOC platform. The course covers basic descriptive statistics, the normal distribution, sampling and hypothesis testing, including t-tests, chi-square tests and ANOVA. The course has no prerequisites, although you may need to spend some extra time learning the basics of R if you haven't used it before.
Each week of Foundations of Data Analysis begins with a reading assignment, a couple of lecture videos with comprehension questions and an R programming tutorial. The videos tend to be in the 7-10 minute range and the tutorials typically total less than 10 minutes a week, so the total video content per week is usually 20-30 minutes. The videos are generally well-edited and the professor does a good job describing concepts simply and concisely. Each week has a prelab, lab and problem set that allow you to apply the concepts you learn in lecture and in the R tutorials. Each problem set consists of 3-4 mini case studies, so you'll probably end up spend most of your time on the labs and problem sets. The assignments are not very difficult, although many questions limit you to 1 or 2 attempts. You need a cumulative score of 70% to earn a certificate.
Foundations of Data Analysis introduces new concepts at a relatively slow pace and gives students a good amount of practice through the labs and assignments. Concepts are explained well in lecture so the readings are not always necessary to do the activities, but they often provide extra depth and raise considerations that are not discussed lecture. The course did have some hiccups with homework questions and auto-graders and many answers expect rounded answers, which can result in frustrating off-by-a-fraction errors. In addition, the course uses an external forum system called Piazza instead of the normal edX forums, which I found to a hassle.
Bottom line: UT.7.01x is a great place for a beginner to start with stats and R as long as you don't mind an external forum.
I give Foundations of Data Analysis 4 out of 5 stars: Very Good.
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