I have to admit, that most of the videos confused more than they helped. For most of the topics I simply went to KhanAcademy and got it easily there and I was asking myself, why a topic was made so complicated. I have the same issue with the next course. I highly recommend to start visual explanations of what you want to achieve instead of throwing formulars at people and confuse them. IN KhanAcademy e.g. they do exactly this and you got the point and if you got the point, the formular wasn't such a big thing anymore.

The content of the course was well organized and structured, but the content delivery in the videos was terrible. I was unable to understand even the basic concepts from the professor due to his fragmented sentence structure, lack of lecture planning and an emphasis on evaluating R code more than on explaining the concept. I am now hesitant to go on to the next course in this specialization. The Swirl() exercises, however, were very thorough and did a good job in explaining the concepts.

Terribly confusing, and concepts were made so much more complicated than needed (lectures, instructions, quizzes).

Most other sources (Khan Academy, Stattrek, Stats textbooks etc) were used and preferred to complete course, to completion of the Data Sciences specialization. Or just have a full understanding in Statistics prior to this course.

Additionally, there's little discussion or help; wish this course could've been updated with revisions or clarified over the years.

completely missed the explanation part of the teaching. Why use n-1 for standard deviation? "Because of degrees of freedom" Only mention, no further explanation. Just no explanations of anything in this course. I looked at the biostats course by the same guy. Same story. Teaching is more than just saying the facts, you have to explain things, lead the understanding. The materials are just not there, not in the book either.

If I wasn't already familiar with statistics, I would find the lectures and course book difficult to follow. If future revisions to the course are made, consider including a cheat sheet with the notation, parameter abbreviations used, etc. It would also be helpful to rewrite (or at least include a reference back to) the equation being used in the example calculations instead of immediately filling numbers in.

The instructors approach in this course is very cursory. He tries to split the difference in going through the mechanics/mathematical theory and practical applications. As a result, he fails at both. I think it would be better to leave the mathematics and application learning to supporting materials and focus on explaining the theory and concepts of statistical inference in the lectures.

The hardest course I have ever taken! Very hard to follow! Spent a lot of time, trying to understnad the lectures! The final assignment was really good, it really tied everything together! But the lectures and following them was a nightmare and hard to understand! I spent 55 hrs on this particular course! and the last week 4 I spent 20 hrs on this course

The course is very technical and needs a) reading and practice outside of the material presented here and, b) needs you to invest a lot more time than you might believe before you start this course. So if you are looking to just understand the basics of statistical inference or if you don't have a background in statistics then this is best avoided.

This was a difficult course to get through. The lectures were almost completely useless - I had to look up videos from youtube and other sources for every single lecture to learn the concept, and then rewatch the lecture - even then the instructor was difficult to follow. If this wasn't part of the specialization I would have dropped the course.

Good material but the lectures are not well put together for the novice. I think the professor needs to have a little more empathy for the students and not just read notes for the class. Too many sentences with esoteric terms are spewed out without truly trying to explain the material in a way that the student will understand.

this is heavy material, and I suggest it be broken down to two separate courses, and the author take his time in explaining the various concepts in much more detail vs. trying to cram them within 5 or 10 minute sessions. I know I wasn't the only one struggling to keep up with the teacher after week 2.

The content of this course is interesting and i learned a lot BUT it's indeed badly explained, and i lost a lot of time to understand certain things. My advice: watch others videos (from Khan Academy for instance) in order to understand the basics concepts and then, come back to this course.

Sorry to say, but for me as a non-native english speaker, most videos are hard to follow. Its because speaker talks fast, unclean and with bad sound quality. Of course I'm not used to the mathematical english terms. Also the many animations with the slides made it hard for me.

It may be that this is the first Math heavy course in the data science specialisation, but I found this one really hard going, with the videos being particularly hard to follow. I had to do a lot of extra research to find alternative explanations of the concepts involved

Doesn't really teach you stats, gives you a rough idea but only shows you that it's possible in R. Doesn't really explain what it's doing or how to do it, rather "here's a handy R function that does this". Meaning I'm just learning R rather than any actual stats.

True the content is rich, but the instructor is not engaging and much content is not well explained so the learner should search everywhere. If it is to compare with khan academy videos for example, they are much more coherent and way too easier to understand

To someone new to statistics, this course does NOT help. The professor does not seem too interested or enthusiastic and seems like he is reading off the slides. Concepts are not explained clearly at all. Forced myself through this course :(

Despite the pertinent content, the way the instructor gave the classes could have been way more intuitive. You'll find videos on the web that can help you with the subjects covered and do a better job explaining the concepts. Disappointing.

Some concepts are advanced and it requires detailed knowledge of statistics. It would be good to add a chapter to explain the basics before going through advanced concepts. The explanation in some of chapters are very basic.

This course should not be presented by video. I loose lot of time by learn with others supports than Coursera.

Even if I notice and appreciate the works to produce these supports by the teacher, I'm not a big fan at all.

this is a difficult subject that takes a lot of practice to understand. would like to see the course time and materials extended. It would also be helpful to have live online sessions with instructor and classmates.

I think the course was very informative but it took me about 3 months to finish course. Lot of important concepts have been condensed to one or two slides which makes it really hard to grasp the concept quickly.

This course is great, but Brian is certainly not a good instructor. He does not explain things well, and articulate examples. I had to take Statistical Inference from Duke university to pass this course.

This course is poorly taught. The instructors often speed through significant concepts and are generally unable to explain the concepts clearly to someone who does not have a major statistics background.

Taught very quickly and assumes a high degree of math fluency. Only take this if you are either very fluent in math already or have a significant amount of time to devote to understanding the material.