PB
Very concise, well-presented course. This was my second time taking it as a refresher. Prof. Caffo does a great job presenting the materials. However, prepare to be challenged.

Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression. This specialization starts with Mathematical Statistics bootcamps, specifically concepts and methods used in biostatistics applications. These range from probability, distribution, and likelihood concepts to hypothesis testing and case-control sampling. This specialization also linear models for data science, starting from understanding least squares from a linear algebraic and mathematical perspective, to statistical linear models, including multivariate regression using the R programming language. These courses will give learners a firm foundation in the linear algebraic treatment of regression modeling, which will greatly augment applied data scientists' general understanding of regression models. This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.

PB
Very concise, well-presented course. This was my second time taking it as a refresher. Prof. Caffo does a great job presenting the materials. However, prepare to be challenged.
VS
This is amazing course for reviewing categorical statistics.
JC
Very thorough and rigorous. A great review for me.
ML
Good course on applied linear statistical modeling.
MC
The content is in-depth and the instructor is knowledgeable, but the quiz demands a quite wide knowledge base and does not provide feedback.
LC
The course is extremely structured. It is a fantastic "boot camp" for students who would like to learn statistics, opening the door of future data analysis.
CL
The course is interesting; but is more theoretical in nature than applied.
N
It is a very good course for any statistics to learn and have a sweet tastes of math and its behind functionality on data.
AB
Thank you very much for your course. It is clear and to the point. But it was very difficult to perceive a video-lectures of 30 minutes.
AA
The material is very helpful, plus the exercises and assessments use analysis and analogical language that are very challenging.
JL
I really enjoyed the course. It was well explained and the quizzes at regular intervals were helpful. It would be great if there were some practice exercises though...
RL
Great !!! Learning time and I enjoy the math side of it...
Showing: 20 of 121
Interesting topic. You just need a basic high school level mathematic background (derivative, integral, set theory) to succeed.
I learned many things and for that I am grateful and that's why I have given 3 stars, *BUT* it was suffering to follow this course due to the lack of pedagogy (my opinion). Even if the teacher apparently tried to be didactic, he failed in my opinion.
The slides are mostly text and formula, no schemes, no tables, no animations, almost entirely black and white, nothing to help visually. If you are not an auditory memory person, you are in the bad lecture. The content is easy and basic, but the way it is presented is rather harmful. Fery few examples. The homeworks and quizz are pertinent but there is not enough questions, not enough exercises to try our understanding. And the corrections are really minimalist or even inexistent. I did not catch the objectives of most of the lectures, the motivations was not relly explained neither the link between the lectures. I found that the structure was not adequate for this basic level of statistic course.
The interpretations of the claims and results are very poorly explored, that's a shame because when Brian Caffo rarely covered interpretations, it was very interesting because he gives us many details about the different way of interpretation and the strenghts and weakness of each interpretation.
In conclusion, this COULD HAVE BEEN an excellent AND pleasant course, but for that you have to consider the question "How could I understand sufficiently well and present sufficiently well my lectures and each slides and each exercise and each example and each question (... ...) such as someone that never heard about this topic and that does not have my background and experience can understand deeply what I am saying without the need of exterior help?" Especially for a MOOC.
Despite all of these points, I repeat nevertheless that I learned many things and that I am grateful for the content and the initiative and the work that was done to prepare and realize this course (I am totally aware how much work and time it takes).
For prospective students who are looking to enter the biostatistics/epidemiology field in the future. This course is designed as an in depth fundamentals of biostatistics where Professor Brain Caffo dives deep into some of the key formulas, origins of statistical formulas, and theoretical aspects of statistics.
Great lecture with valuable information, however, due to the lack of engagement within the lectures, it absolutely leave students who have no background of Calculus or Linear Algebra in the dust with no reference to assist them in the course. Once or if a student has a solid foundation for the topics covered in this course, this information is very insightful and understandable.
you might ask yourself, someone who doesn't have a prior knowledge of the material covered in the course if you should even take part in the course, my answer would still be yes, so long as you are willing take notes, save the videos, and return back to them at a later point once you build yourself up by studying calculus, statistics, and/or linear algebra.
I'd previously done stats a few years ago, I came to this course to refresh my knowledge. Practice problems can't be done based on lecture videos alone, and take much longer to do than advertised.
Undoubtedly the course instructor is very knowledgeable. However I did not take away as much from this course as I would like to. It is mostly theoretical; very limited examples. I also missed the bio in biostatistics. A title like "Mathematical Statistical theory boot camp" would be better suited. I believe having a set of cases that get reused in some form over all lectures would be very beneficial for -at lease mine- understanding the topics. The form of lecturing is not using the benefits that an online platform offers. So instead of short interactive videos, this has slides with lengthy essential spoken word with it; hardly summaries.
He terribly prepared us for quizes and gave about 4 examples in the entire course. I filled a notebook with about 40 pages of notes, about 3 of which were useful for the quizes. Though content was good, but i found myself looking things up because of his somewhat neive explanations of difficult concept.
No responses to the discussion forum. Looks like the prof has just left the course like an orphan, and does not take responsibility.
The only plus is, I find the assignments challenging, which really help me reinforce the concepts. No solutions though, so I'm left wondering what's the right way to do some of them.
The lectures are monotonous and simple reading from ppt. Would recommend ONLY if you're looking for challenging assignments.
This is a very worthful course to SUFFER! I'd like to say, no camp, no gain. In addition to the statistics with math, I experience how important of "hang on there and never give up"!I'm going to the camp 2 to see what's gonna happen.
Lectures are a bit confusing. I watched youtube videos for better explanations.
Lot of material to cover obviously and bridging theory to practical skills and knowledge is a tall order. But this course finds a way to force the learner to really understand some fundamental statistical concepts through brilliantly designed, albeit very challenging, quiz questions. The lectures are as straight-forward as you could ask for without compromising the integrity of this being a purely statistical course. If you're looking to establish a basic foundation in statistics, I strongly recommend this course without reservation. Recommend students take the math requirements seriously (algebra, integral and differential calculus).
Brian Caffo is the best statistics teacher I have ever had. I like how he breaks down things and he covers the ways to think about statistics far beyond any course I have taken.
推荐之前修过统计基础课程的人上,最好还学过一点R。
I learned a lot in the course. I'm not sure that Dr Caffo is the best explainer ever, and there could be more worked examples. Or maybe extra quizzes?
The lectures provide inadequate information to complete the homework, and the quizes provide no feedback. There isn't enough practice/sample questions given to solidify the material being quized over.
This is a very rigorous course. The problem sets and quizzes require a good grasp of calculus and ideally some prior exposure to statistical concepts. The lectures are clear and were a fantastic review of the material at an advanced level!
Excellent course. I thank Prof Caffo for creating this content rich course and explaining it in an utmost lucid manner, that even person with average mathematical background could also grasp the idea without much difficulty.
Very nice and informative course, with really interesting examples. I like Brian's lectures and his humour and I find him very knowledgable and informative. I would definitely recommend this course.
I knew a lot about probability before starting this course, but I didn't know much of anything about frequentist statistics. This course helped me understand some tricky concepts.
Very concise, well-presented course. This was my second time taking it as a refresher. Prof. Caffo does a great job presenting the materials. However, prepare to be challenged.
Great course, though a little difficult in parts, particularly the first week. Worth working through though for a better understanding of probability and statistics.
The best Coursera has to offer. Excellent instruction & coverage.