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.
Introduction, Probability, Expectations, and Random Vectors You are about to undergo an intense and demanding immersion into the world of mathematical biostatistics. Over the next few weeks, you will learn about probability, expectations, conditional probabilities, distributions, confidence intervals, bootstrapping, binomial proportions, and much more. Module 1 covers experiments, probability, variables, mass functions, density functions, cumulative distribution functions, expectations, variations, and vectors.
Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics This module covers Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics. These are the most fundamental core concepts in mathematical biostatistics and statistics. After this module you should be able to recognize and be functional in these key concepts.
Confidence Intervals, Bootstrapping, and Plotting This module covers Confidence Intervals, Bootstrapping, and Plotting. These are core concepts in mathematical biostatistics and statistics. After this module you should be able to recognize and be functional in these key concepts.
Binomial Proportions and Logs This module covers Binomial Proportions and Logs. These are core concepts in mathematical biostatistics and statistics. After this module you should be able to recognize and be functional in these key concepts.
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.
I apologize in advance for how angry this course makes me. It is teaching like this that makes people believe that math is inherently difficult or that you have to have a certain mindset to do math. That simply isn't the case at all. I have a degree in math, teach statistics and have considered becoming an actuary. I know my statistics! Still I found myself being confused as to what exactly Professor Caffo was trying to say at times. I have no doubt that he is able to teach this stuff well at Johns Hopkins but Prof. Caffo seems oblivious to online learning.
My absolute biggest problem with this course is not the length of the videos, or the poorly designed slides. It is the lack of problems that really makes me mad. The only way to learn math is to do math. That is it. There is no other way. You can watch all the video lectures you want and read all of the math books in the world. If you do not do problems you will not master the material.
Brian Caffo is a terrible lecturer, and I can say that with experience after completing MBB1 and still taking MBB2. As a result, these courses are very difficult to do, especially because I am learning statistics for the first time.
He stumbles often, which makes it hard to follow him, but most infuriatingly, he goes off on tangents, and then I lose him.
I often question whether I've learnt anything at all from these two courses. I definitely do not recommend Caffo as a lecturer nor recommend these courses if you are learning statistics for the first time; you will be lost!
Hchancompleted this course, spending 2 hours a week on it and found the course difficulty to be easy.
This class moves extremely quickly over the high level topics of statistics. It is focused on applications and there are very few derivations or intuitions. I would advise not attempting this as a first statistics class. Instead, if you are new to stats, learn statistics from a more comprehensive intro class (there are a large number of these available from various platforms like Udacity, Edx, and Coursera). This course is most helpful if you already have prior exposure to the basic concepts of statistics but want a quick refresher to bring yourself back up to speed. In the latter sense it can be quite helpful.
- 3 attempts for quizzes (reduces exam stress a bit)
- helpful CTAs
- some lectures a bit long
- Prof Caffo digresses a bit in some
- the biggie: not enough practice questions (160 inc h/w & quizzes for whole course)
Perhaps very bright people can get a firm grasp of introductory math stats with only 160 practice questions in total (& worked solutions for only 80 of these). I don't think I can, but regardless this has the makings of a good refresher/intro if you have access to a textbook with more solved questions - I'm looking for a cheapo old edition right now!
Adelyne Chancompleted this course, spending 6 hours a week on it and found the course difficulty to be hard.
I took this course because I felt biostatistics would be interesting and useful for me as a biology student, struggled a little with the concepts but Prof Caffo did a good job of explaining and the exercises / assessments are very reflective of how well you know the material - makes it very easy to identify areas which need to be reviewed.
Am looking forward for Biostatistics Boot Camp II to be offered at a time that fits my schedule so I can take the follow up to this course!
I have taken graduate level biostats online through a traditional program and done well. Biostats is a difficult subject, so I thought the Biostatisical Bootcamp course would be a good review before I took further classes. In Bootcamp, there is a huge emphasis on calculus that I didn't anticipate. None of the course descriptions mentioned a need to know calculus. I am hampered at the moment by trying to learn the calculus required to complete the quizzes.
I am currently a Sophomore in High School and with Coursera I have already taken two courses, Calculus 1 with Jim Fowler and Computer Science 101. I loved these two and finished with As. When it comes to this course, I felt it was horribly explained and Mr. Caffo provided no examples with these complicated topics and was disappointed at the lack of preparation, explanation and explicitness. Although I did like his course topics and felt it was well planned.
I liked this course very much, because I was interested in the math behind bio-statistic. This course was challenging and I spent more than 8-12 hours a week to understand the material. I have done afterward a biostat-course in a masters programs, and I can tell the difference. Brain Caffo did an excellent job!
Clearly more than intermediate class which tends to mathematics statistics, but very well documented and presented materials by professor Caffo. Moreover, not usual exercises for careful students and in most of the examples was used R language.