For my third online course I opted for Statistics One - a 6-weeks introductory course on Statistics.

My choice was influenced by two factors: first of all some basic statistics have been part of all the course I took, and I am also planning to get another course focusing on Data Analysis, because it may help with some problems I need to analyse for job-related problems.

So in general I think that Statistics provide a good foundation and will probably play a key role in future studies.

The other reason was a bit more practical, even if in the end it's again a first step in the same general direction: this course had all the "homework" based on using "R".

So you get to learn the basics of it and play around a bit with data sets provided as part of the course material.

On the other hand, I persevere to invest the minimum amount of time possible to follow the lessons and send in the homework before the deadline. This is always complicated because I have plenty of things to do (including, at the same time, some other kind of studying, plus Aikido, Shodo and work…).

**Final Result: 85%**(by counting only the midterm and final exams). Usual caveats apply: course not very hard, so anyone with more energies/time to dedicate to this will surely fare better.

The "R" part was very interesting. I focused only the parts actually needed for the homework, but having a good experience as a developer I think I would have little problems in "grokking" more of it if needs arise, even if lots of people in the forums complained about "R" being hard to use or just plain weird.

**Schedule:**

__Week 1__

- Lecture 1 ~ Randomized experiments vs. Observational studies
- Lecture 2 ~ Descriptive statistics
- Lecture 3 ~ Introduction to R

__Week 2__

- Lecture 4 ~ Correlation
- Lecture 5 ~ Measurement
- Lecture 6 ~ Correlation analysis in R

__Week 3__

- Lecture 7 ~ Regression
- Lecture 8 ~ Multiple regression
- Lecture 9 ~ Multiple regression analysis in R

__Week 4__

- Lecture 10 ~ Mediation
- Lecture 11 ~ Moderation
- Lecture 12 ~ Mediation & moderation analysis in R

__Week 5__

- Lecture 13 ~ Student’s t-test
- Lecture 14 ~ Analysis of Variance (ANOVA)
- Lecture 15 ~ ANOVA and t-tests in R

__Week 6__

- Lecture 16 ~ Factorial ANOVA
- Lecture 17 ~ Model comparison
- Lecture 18 ~ Factorial ANOVA in R