#105 overall
Intro to Statistics
Udacity
4 recommenders · 4 threads · recommended in 4 years, 2012–2019 · score 4.2
An introductory Udacity course on statistics, taught by Sebastian Thrun, covering basic statistical concepts for data analysis. Commenters also mention companion Udacity courses on descriptive and inferential statistics.
Commenters call it an informative, easy-to-follow introduction to statistics that helped one person move into data analytics and brush up on stats skills.
Recommendations by year
20062026
I completely agree. Udacity was the one that helped me move into my career in data analytics. I took Thrun's excellent Intro to Stats[1] class to brush up my Stats skills along with some other courses such as Intro to Descriptive Stats[2] and Intro to Inferential Stats[3].
[1] https://www.udacity.com/course/intro-to-statistics--st101
[2] https://www.udacity.com/course/intro-to-descriptive-statisti...
[3] https://www.udacity.com/course/intro-to-inferential-statisti...
@ArkyBeagle Thank you for the book recommended!
@smtucker I'm also a math noob, and I'm a half way through Udacity's "College Algebra" (free) course:
https://www.udacity.com/course/viewer#!/c-ma008
There is also a good introductory class on Statistics:
https://www.udacity.com/course/viewer#!/c-st101
After these classes, hopefully, reading "Transition to Advanced Mathematics" will not be a pain.
Check out the Intro to Stats course on Udacity:
https://www.udacity.com/course/st101
Just took it earlier this year. It was informative and I enjoyed the class.
Coursera's Automata course is really good, but it's hard work. It's a six week course, and you'll spend around 10hrs per week if you do everything (and I'd recommend doing everything).
Udacity's introduction to statistics, so far, has been really easy.
From what I've seen so far, Udacity are aiming to be more inclusive "community college" level and Coursera are aiming for a true university level education.
Sorry for the late response, I completely forgot about this post!
Looks like you're on the right track though, "Think Stats" and Udacity's stats class were the main things I was going to recommend. I'd also recommend checking out IPython's web notebook for inline charts and general awesomeness, and the Pandas library for an R-style data frame built on top of NumPy. The best resources for learning about IPython are probably screencasts, and the author of Pandas has a book out named "Python for Data Analysis" that covers IPython, NumPy, Pandas and some matplotlib.