Back to Mathematical Biostatistics Boot Camp 1

stars

487 ratings

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required....

AC

Mar 25, 2023

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.

DH

Jun 4, 2017

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.

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By Omar M B

•Jan 29, 2017

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.

By Xavier S

•Dec 25, 2019

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).

By Soren S S

•Jun 18, 2017

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.

By Mark B

•Dec 31, 2016

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.

By Mitchell L

•Jun 20, 2016

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.

By Joseph L

•Jun 15, 2018

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.

By Vibha H

•Jul 17, 2019

Lectures are a bit confusing. I watched youtube videos for better explanations.

By Deleted A

•Dec 23, 2020

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.

By Charles M

•Dec 8, 2019

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).

By Tarik E L

•Jan 16, 2021

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.

By Mengyu D

•Feb 18, 2017

推荐之前修过统计基础课程的人上，最好还学过一点R。

By Chrys

•Jul 11, 2017

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?

By Douglas B

•Mar 21, 2022

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.

By santhosh K

•Sep 3, 2020

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.

By Phillip A B

•Jan 11, 2016

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.

By Jeremy B

•Jul 9, 2017

Great course, though a little difficult in parts, particularly the first week. Worth working through though for a better understanding of probability and statistics.

By Alexander K

•May 15, 2021

Powerpoint style is suboptimal; it presents a weird problem for the student where it' s more important to listen to what the speaker is saying or to first read what's on the slide. (Sure, I can pause the video, but that interrupts the "flow" in a sense).

Content is great and gives a good sense of how the statistical techniques could be useful in practice. However, in some cases, there is some lack of depth, especially concerning some of the mathematics, (even more particularly, the section on log-normals). I would have liked to see more fully worked examples and not just snapshots of R code which provide some solutions; i.e. it'd be nice to have the thinking broken down instead of presented in one chunk.

Overall, Brian is engaging, and I am very thankful he put this together; I found it very helpful.

By Fan T

•Jan 21, 2022

I like really course content but it would be better to add exlaination for quiz (especially when initial answer is wrong, now student can only see explainations when answer question right)

By Marco C

•Aug 31, 2017

The content is in-depth and the instructor is knowledgeable, but the quiz demands a quite wide knowledge base and does not provide feedback.

By Zack H

•Aug 15, 2022

Great class with great contents, but pretty much all about mathematical statistics, not much bio- related stuffs.

This class is really advanced. It is good for reviewing, but for the peoeple without upper level statistics knowledges, you better not do this course. And since this course has been out for years (from the slides you can see that this was first made in 2012), there is no support at all. Your questions in the discussion forums will NOT be answered.

Even though the video contents are rich, but most of them are NOT useful for the quizes. The quizes always ask you some concepts that are not covered in the videos. By the way, there is no solutions for the quizes, so for the hard questions, you have to ask your own prof to figure them out.

By Michael H

•Jan 11, 2023

The material is great, but there are few things about this course. Firstly, some of the material are well-covered, whereas some others are not (mainly in Module 3 and Module 4). It would have been better to include more mathematics (as well as additional formulas as to assist the students to learn well) and explain notations as well in case there are students who studied mathematics before. and also students who didn't study mathematics.

Other than that, a mediocre course. Not the best course to take, but acts as a good refresher for those with some previous background.

By KJ B

•Jul 27, 2017

There are few quizzes to test skills, and lectures are not interactive. There are better course on this site for statistics learning.

By Alice T

•Dec 4, 2020

Not the best. Presumes a lot of knowledge that people probably don't have, even people in the field. Professor's communication style was pretty indirect and lectures were somewhat confusing and hard to follow.

By Nicolás S

•Jul 6, 2022

If you like those "go find the answer elsewhere" type of courses, go for it.

By Arnold S

•Sep 19, 2023

With an "Advanced Statistics for Data Science Specialization", I expect to gain intuition on statistical concepts relevant for Data Science. However, this course is only about mathematical proof of certain concepts. Expect more explanation about the mathematical meaning of "the limit of N going to infinity for N/(N+1)" and how the outcome is said to become 1, than about _any_ statistical concept you might encounter in this course (well, at least for the first two weeks, because that's when I quit).

For example, it is mathematically proven that the distribution of the average of dice rolls (properly normalized), in the limit becomes that of the standard normal. But, the outcome of a dice roll is bound from 1 to 6 and so is the average. How does this relate to the unbound standard normal distribution? You are on your own to discover that in the normalizing you shift and scale the range of 1 to 6 to a larger range (proportional to something like square root of N), reaching +/- infinity in the limit. But THAT is NOT explained AT ALL! And yes, you _can_ read it in the slides, as there _is_ a formula that divides something by "s/sqrt(N)".