Learner Reviews & Feedback for Inferential Statistics by Duke University

Very good explained course, with lot of useful exercise, so you can be sure to understand the theory. Th practical examples in R are well designed and explained. This is definitely a must for someone interested in statistics, with beginning concepts that you need to keep in mind for further coursers. The teaches is also excellent, explanation and examples are very good. Recommended!

great class, I improved many Statistics skills and learned R at the same time

good course

Very useful and meaningful lectures!

I learned many things from this course.

Thank you.

seeking statistics inference through example in very convenient and easier way

Great course, more difficult than the first module. The code was super useful to learn.

Very nice job of explaining the material. I love the diverse set of examples used in the lectures and labs.

Very rigorous coursework. Loved the material.

Great learning experience. Very well crafted course. Thank you Dr. Rundel and the entire team of instructors!

awesome

Excellent!

It is very helpful to me.

The inference function and hypotheses tests are really useful. Permutation tests need more explaining and examples; otherwise they should not be included.

Generally a great course, but would benefit from a better explanation at times of how to use R effectively.

The course is very well explained I had to refer other materials for ANOVA technique to understand it better hence that part can be either improved OR more reference material be provided

Great material although I will like to know more about the practical side of statistical inference. For instance, I have more of less an idea of how to use chi-squared test with categorical variables in a dataset however, for the other statistical inference methods such as p-values and confidence intervals I still don't see where can I use this methods when doing data analysis. Can we use this to detect outliers in our dataset for instance?

excelent

Its a very good way to introduce to R language

I wish there was more exposure to R.

Very good material which gives practical knowledge supported by interesting examples. The only concern is that it is slightly shallow - lacking some mathematical justification for the given "rules of thumb" and theorems.

Need to revisit few classes as it was little aggressive.

Nice introduction to statistical inference concepts and techniques

This is great course as Intro to Statistics

Some parts are needed more clarification. In other words, as a student of the course you need to go beyond the materials, since the materials are not self-sufficient. Specially about simulation methods. However, this is not the reason that I give the course 4 out of 5. The absence of any help from TAs, based on my experience, is the reason. I expected some official replies to my question while there are only a few question for each week of the course.

I liked this course because it gives basic ideas how inferential statistics works, without going into mathematical details.