This course covers the most popular statistical ideas (it closely follows the O'Reilly book "Practical Statistics for Data Scientists"), so the material is relevant. Unfortunately, the course is not designed well for comprehension. The instructor glosses over things very quickly, and fails to define crucial terms and concepts. For instance, he never once says "this is the formula for deriving the standard deviation," instead he only ever says "now we will standardize" and you need to know what he means. When calculating probability in the early lessons, he does not pause to help you learn how to assign A and B, nor does he stop to say which values he has assigned to A and which to B. As of May 2020, halfway into what I believe is the first iteration of the course, the Forums were not turned on so we cannot seek help from our classmates, even though about 3,000 are currently enrolled. I'm five weeks in and completely undecided about whether to continue or not; I am not learning statistics; for the most part I am just retaking the tests over and over again until I pass. Please at a minimum turn on the forums for students. But also consider re-recording the Probability section to include more instruction about how to assign variables to A and B, and to more clearly specify what the teacher considers to be A and B in the course examples. IAlso, if the profession consistently uses the phrase "standardize" to mean "calculate the standard deviation" please say that somewhere. n addition, the Week 3 Quiz includes a question not covered until the Week 4 material.

It's an Introduction to Statistics and it means it should help those who are new to statistics. But it's way far from that.

The instructor explains topics very very very very and again very summarized. While he drops mind boggling formulas on to the screen, he explains you the 1/100 of the tip of the ice berg.

You just cannot use this course for an introduction to statistics. You need a lot of books and a lot of time to get the quizzes right.

I've completed 10 modules. However I decide to stop learning statistics here although I've passed the 10 modules with high scores.

I think the learning materials of this course are valuable and the instructor, professor Guenther Walther is excellent. However, for global students, this course is awful, comparing with the other beginner level courses in Coursera, A lot of concepts in the videos are not introduced clearly, for example, what is median? How to find the median? How to distinguish dependent variables from independent variables? What is a sample? What is a category? What is replacement for a draw? When should be replacement? I think the instructor assumed every student here is a Stanford student or an American student.

To be honest, this course is not supportive to students because it doesn't open the discussion forum for students to discuss the problems coming from the materials and correct the incorrect calculation in the instruction. In addition, there is not any handout to help students to summarize what are taught in the module or give more examples. Only quizzes, but no exercises. These makes the learning here generate a lot of difficulties and failures despite there are explanations following the quizzes.

In spite of that, I will miss the voice of professor Guenther Walther. The voice sounds sincere and friendly.

I will come back when I think I can continue to learn here. Hope this course will be improved in the future.

No proper explanation of concepts, no in detail examples, no proper set of quizes,content is lagging

I'm disappointed that this course is listed as an introduction, when the professor does not treat it as such. He glosses over important information and does not care to explain in any detail. I had to search for Conditional Probablility on youtube just to grasp the concept. The professor didn't care to explain the one example he gave us in any detail. I'll come back to this course after I've taken a real introduction to statistics. This is NOT for beginners.

The lecturer is extremely dry and the course materials contain many gaps. Concepts are discussed without having been properly introduced.

Enjoyed the course but had repeating problems with the Coursera platform not submitting quizzes for weeks. Coursera provided no support and no communication (zero). Had to contact Stanford administration to get any action on the problem. Still Coursera did not communicate and were slow to respond to the school administration. Finally fixed two days before course deadline.

Critical bugs in the Coursera platform. Absolutely no response from Coursera to flagged bug reports. Absolutely no Coursera support. Cannot recommend.

This course should not be called "Introduction to Statistics" but rather a refresher, which would imply that you already know everything about statistics, just need to remind yourself of a couple of things. Otherwise, the course is not self-sufficient to teach the concepts of statistics and to make you use them.

Week 1: very fast, but manageable

Week 2: very fast, lacks explanations, not complete information to solve the test. In the examples, it was not clear what A and B represent. Later, during the test, I could not even manage to assign propabilities. For example, could it be the probability of "known answer" in "correct answer" or "correct answer" in "all answers", how to take into account the total number of questions and the fact that only the first question was solved. Disaster!

I do not expect that knowledge shoul be handed on a silver platter (while the general concept of MOOCs is about an affordable way to learn new skills), but I do not want to go through the tons of books till I find the one corresponding to this course. If the authors wanted to keep the level high, why not to suggest extra reading?

Besides, there is a thechnical nuances in the videos: quiz questions pop up before you finish listenign to the explanation and manage to see the formula.

Most probably, I will quit before starting Week 3...

I really good introduction course. The weekly lecture and quiz time commitment is very manageable. The lectures/quizzes focus more on the theory rather than the number crunching.

I didn't care for this course, as I found myself spending most of my time learning the material outside the class. I'd recommend the Khan Academy AP Stats course as a step up. Some of the biggest issues were:

1) The style was pure "monkey see/monkey do" where he stated a technique and then plugged in numbers. He often provided no intuition or mathematical rigor as to why they work. Understanding the "why" is key to long term retention of the information, and I found myself having to spend a lot of time outside the course to learn that.

2) There are no labs to get hands-on practice trying the techniques in Python or R or some other environment.

3) Week 6 (bootstrap) was particularly bad. I would suggest removing that from the curriculum as it is beyond saving and isn't core to the curriculum.

4) Some important techniques, such as defining alpha and beta levels for a test and how to adjust the tests to meet those goals, was not covered at all. In fact, type 2 errors was not covered.

5) Those are the main reasons for a 1 star review, but I want to add; some of the pop-up questions in the lessons ask detailed questions about the slide being shown, but the pop-up covers the slide. Please make sure there is enough context in each pop-up.

The course, called "Introducion" of Statistics, is actually an ADVANCED course. A deep and solid math knowledge is required in order to understand all the topics in the course.

I like the content and how the course was divided but spent most of the time looking for clearer explanation on youtube. Explanations are very vague. I wished they had more details and showed how to 'compute' instead of just showing the result. I would also advise on more quizzes and examples. In my case, It was very discouraging to look elsewhere for a fully paid course. I'd not recomend this course for a beginner with no notion of probability.

This is NOT an introductory statistics course. I have taken a couple statistics courses already and this course discusses ideas which a beginning statistics student can no way possibly understand fully. If you want an introductory statistics course this course is DEFINITELY NOT the one to take. There are other choices out there that are much better trust me. My suggestion is take an online statistics course directly from the university itself or look into statistics.com. You will have a much better educational experience in these other places in my opinion. Coursera is fine but not in this case.

The course content presenter is very experienced and he presented the material in very intutive way. Thank you very much Sir for sharing your knowledge and experience.

I don’t understand why we were given two questions on the quiz that we were never taught to solve. I really would have appreciated the instructor giving a few example problems and step by step solution methods. I am going to wind up dropping the class because the teaching method of skipping over processes is completely ineffective, and it is demoralizing for those with math disabilities. That is why I took a beginner class in the first place.

Please, for the sake of your students, address that shortcoming in order that those who are no math professors may learn. Setting up your beginner students for failure is completely unfair and unkind. Thank you.

Greetings, don't be tired, thank you dear professor for your efforts in the courses I hope you are healthy and happy. Mohammad Pakzad from Iran

Thank you for read my text

This is an excellent course both for beginners and those who would like to refresh their knowledge on basic statistics. The course is very interactive and of high standard.

Very confusing. I'm used to seeing derivations and logical sequences of how concepts progress from one to another. This is an incredibly frustrating course with large gaps which can only be filled in if you've studied this before, in which case you wouldn't need to do this one. How is the correlation coefficient related to the linear regression formulae? Where's the algebra? Why can you use x to predict y, but not use y to predict x? Has it got something to do with covariance, whic I just read up on?? Who knows.

I know this is a condensed version of the subject, but sometimes going into more depth can help explain things so that you understand them and in turn make the subject easier.

I would not call this beginner at all. You get a short 5-10min lecture and then are expected to apply a concept in a quiz. A concept that you aren't really truly taught in the lecture. There are no exercises or practice to learn and comprehend the subject of each week's lecture. After 4 weeks of trying to make a go of this course I am unenrolling as I feel it isn't teaching me anything. I have had to go to other outlets to research and learn only to return to the quizzes and try and answer questions. How this course is so highly rated is beyond me as I see the course discussions also show other students having same issues as myself.

INSUFFICIENT LECTURES

Extremely rushed course with few examples and just slides of monotenous droning over formulas thrown on screen.

I am thrilled to share my five-star review for the "Introductory to Statistics" course offered by Stanford University through Coursera. This course has exceeded my expectations and has been an incredible learning experience.

Professor Guenther Walther, with his vast knowledge and expertise in statistics, delivered the course content in an engaging and comprehensive manner. His ability to explain complex concepts in a clear and understandable way truly made a difference in my learning journey. I appreciate his dedication to providing a high-quality educational experience.

The course structure and materials were well-organized, allowing for a smooth progression of learning. The interactive quizzes, assignments, and real-world examples provided a practical understanding of statistical concepts. The course also offered opportunities for hands-on practice, which solidified my understanding of the material.

One aspect that stood out for me was the strong emphasis on application. The course not only focused on theory but also provided practical scenarios where statistics plays a crucial role. This approach helped me see the real-world significance of statistics and how it can be applied to various fields.

I would like to express my gratitude to Coursera and Stanford University for their collaboration in making this course accessible to a global audience. The platform was user-friendly, and the course materials were of excellent quality. The availability of discussion forums and the opportunity to connect with fellow learners added immense value to the overall learning experience.

Completing this course has equipped me with valuable statistical knowledge and analytical skills that I can apply in my personal and professional life. I am confident that the concepts and techniques I have learned will have a lasting impact on my decision-making processes and problem-solving abilities.

I wholeheartedly recommend the "Introductory to Statistics" course to anyone interested in gaining a solid foundation in statistics. Whether you are a student, professional, or simply curious about the subject, this course will provide you with a comprehensive understanding of statistics and its practical applications.

Thank you once again to Professor Guenther Walther, Coursera, and Stanford University for offering this outstanding course. It has been an enlightening journey, and I am grateful for the opportunity to expand my knowledge in such a meaningful way.

Excellent content - explains complex concepts in simple words. Though i had prior knowledge of statistics and i undertook this course as part of the Foundation in Data science course, i found this excellent content.

I started this course to get into machine learning and AI. This was packed with a lot of information to get you started. It doesn't got deep into each topic but great for an overal view.

The material is very, very superior. The pop-up quizzes are a great way to keep attention hooked. The end of topic quizzes require comprehensive understanding of the topic.