Mar 02, 2017
Excellent course. The lecturer has written code snippets that let the students visualize the meaning and interrelationship of p-values confidence-intervals power effect-size bayesian-inference.
Feb 22, 2018
Excellent course with a lot to learn. After 10 years in data analysis it provided me with great new insights and material to further improve my skills and understanding of data analysis
By Daniel K•
Jan 15, 2019
Thanks to the creators of this course for putting together an engaging curriculum. One note of criticism is that the assignments for Week 5 required G*power software which as far as I can tell is not available on Linux (I'm running Ubuntu).
The practical examples, specifically the example of the impact of Facebook's A/B testing were particularly interesting. I think this course has improved the tools I have at my disposal for interpreting the language commonly used in academic reporting, and I'm confident the information and tools presented will help in my own research in the coming years.
By Alicia S J•
Nov 11, 2018
Good pacing and ratio of exercises/lecture. I found the assignments very useful and the instructions easy to follow. Comparing my performance on the pre-tests and pop quizzes at the beginning of the course to those at the end clearly demonstrates that the coursework honed my stats intuition, and I'm very grateful! The only critical feedback I have is that occasionally, I found the wording of test/quiz questions to be a bit confusing. Thanks!
By Marija A•
Oct 12, 2018
I find this course very useful, since these are topics that do not stick when you are completely new to statics, but are very useful once you have few years experience in practice. My only remark is that sometimes the multiple choice answers in the quizzes were not clear enough, so a bit confusing.
By Robert C P•
Jan 21, 2018
This course is a great complement to other statistics related courses. Instead of spending time on a bunch of formulas, this class is more about best practices and how to (correctly) apply some of the basic statistical methods.
By Lior Z•
Oct 10, 2018
Great course! Highly recommended.
One thing to improve - I would like to see more theory behind the different effect sizes (eta-squared/omega squared/etc)
By Ramón G M•
Apr 23, 2018
I recovered my faith in statistics with this course.
Makes me alert not to believe every effect I see in the data.
Teaches to do good science.
By Max R•
Nov 29, 2019
It was nice. I initially hoped the course would have made some technical details intuitively graspable, but it was fine as it is.
By Mage I•
Jun 20, 2018
The course was very useful, I enjoyed Daniel's advice. However, I wasn't able to make R work, so I couldn't do the exams.
By Sanne D•
May 27, 2018
Questions are sometimes hard to understand if you are not a native speaker of the English language
By Leanne C•
Jan 03, 2019
Very informative course, well taught and with lots of useful practice built into the assignments.
Jul 29, 2019
By Yao Y•
Nov 27, 2016
The video is ok, but it lacks a lot of details in calculation. The assignment is very confusing because some questions refer to some 'previous' statement while fail to clarify which is related.
By Emmanuel k A•
Jun 21, 2019
I started just today and I'm beginning to love the course
Sep 21, 2018
I dropped the course at Lecture 1.2 when it was supposed to really teach me what is p-value but it failed. A 20 min video without telling much about p-value and also adding more confusion and unanswered questions at the end. Like what is p-value distribution?
I expected to receive a decent step by step tutorial on statistics starting from basics but it was just another convoluted stuff on statistics.