Mathematical Biostatistics Boot Camp 1
Below are the top discussions from Reddit that mention this online Coursera course from Johns Hopkins University.
This class presents the fundamental probability and statistical concepts used in elementary data analysis.
Statistics Confidence Interval Statistical Hypothesis Testing Biostatistics
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Taught by
Brian Caffo, PhD
Professor, Biostatistics
and 12 more instructors
Offered by
Johns Hopkins University
Reddit Posts and Comments
2 posts • 31 mentions • top 12 shown below
21 points • geebr
Cover the basic distributions  Gaussian, binomial, Poisson, chisquared, exponential (these latter two are both just special cases of gamma). Develop a good understanding of confidence intervals, summary statistics, p values, and moments of distributions. The central limit theorem is enormously useful so make sure you have a good handle on that. Understand hypothesis testing using both parametric and nonparametric approaches. That means also understanding bootstrapping, permutation tests, and Monte Carlo simulations. In my experience, you need to have enough background to find a satisfying answer to the question "what does chance look like?". In my head at least, those concepts form the core of a data science stats curriculum. I heartily recommend Mathematical Biostatistics Bootcamp for getting a better understanding of distributions and hypothesis testing. The course doesn't really cover nonparametric methods much though, as far as I can remember.
12 points • adventuringraw
I found value in this course, but to be honest... I think a MOOC is likely a poor way to learn math. After all, whatever you're learning (math, coding, whatever) your main learning time is when you're in the trenches solving problems, ideally with access to help when you need it. For CS stuff MOOCS seem great. A class based around what amounts to 10 problems (code up the feed forward and back propagate part of this neural network. Use this technique to predict this target variable with this data set, etc) all take a fair bit of time, and get you thinking about a lot of different sides of your craft.
Math on the other hand, it seems like most problems (until you're pretty high level at least) are going to be more run and gun. Your linear algebra will be solid when you've cranked through a few hundred problems covering different techniques, you know? So... what I've done, I picked out some textbooks with accessible solution manuals, a lot of useful practice problems (ideally more geared towards probing deep understanding instead of math busy work) and just... you know. Cranked through. I feel decent about my stats knowledge now, I'm currently working hard to shore up my linear algebra, heading towards matrix calculus. I got a ways into this and realized I need a little more background, haha.
Which brings me to my next thought... math is far easier for me to learn at least, when I have a concrete goal. I'm not actually all that interested in math as a thing in and of itself, but I'm extremely interested in anything that'll give me new insight when solving complex problems. You might find that you have narrow pockets of math you need to pick up now, and don't actually need to go through whole courses or anything.
If you need low level stuff though (basic stats, intro to linear algebra, basic calc, etc.) then Kahn's Academy's probably your best bet, but obviously you'll run way outside the course has to offer pretty quick if you're interested in getting into white papers and such.
8 points • MaiLittlePwny
Coursera do a course https://www.coursera.org/learn/biostatistics/home/welcome bio statistics that uses R pretty heavily. Haven't completed it so don't know how in depth it goes though.
6 points • ruslankl
I enjoyed these two resources:
 Mathematical Biostatistics Boot Camp pt.1 and pt.2 (Coursera)
 Biostatistics and Epidemiology Lecture Series (YouTube)
1 points • sagar_r_parmar
This course from coursera may feel a bit familiar to you based on your background https://www.coursera.org/learn/biostatistics
5 points • AstroZombie138
I am not into biostats, but I thought the biostats bootcamp from Johns Hopkins was interesting (it is a video lecture series, not a book)
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https://www.coursera.org/learn/biostatistics
and some on youtube here: https://www.youtube.com/watch?v=jkUqDVtpKs4&list=PLplgQkQivXhk6qSyiNj51qamjAtZISJ
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15 points • NicolasGuacamole
[Undergrad General] Trying to plan out a selfstudy degree
Hi. I have nearly completed my degree in a different subject and would like to essentially study for a second degree, but this time in Mathematics. The trouble is that I can't afford to study it formally. As such I'm looking to put together a personal course of study. So far, with a great deal of advice I've come out with this:
1st year 

Stanford  Mathematical thinking https://www.coursera.org/course/maththink

MIT  Algebra 1 http://ocw.mit.edu/courses/mathematics/18701algebraifall2010/index.htm

Ohio State  Calculus 1 https://www.coursera.org/learn/calculus1

MIT  Linear Algebra http://ocw.mit.edu/courses/mathematics/1806sclinearalgebrafall2011/

MIT  Intro to Probability and Statistics http://ocw.mit.edu/courses/mathematics/1805introductiontoprobabilityandstatisticsspring2014/index.htm

MIT  Algebra 2 http://ocw.mit.edu/courses/mathematics/18702algebraiispring2011/index.htm

Ohio State  Calculus 2 (Sequences and Series) https://www.coursera.org/learn/advancedcalculus

John Hopkins  Mathematical Biostatistics 1 https://www.coursera.org/learn/biostatistics
2nd year 

MIT  Calculus with Applications http://ocw.mit.edu/courses/mathematics/18013acalculuswithapplicationsspring2005/

MIT  Differential Equations http://ocw.mit.edu/courses/mathematics/1803scdifferentialequationsfall2011/

MIT  Calculus of Several Variables http://ocw.mit.edu/courses/mathematics/18022calculusofseveralvariablesfall2010/

MIT  Partial Differential equations http://ocw.mit.edu/courses/mathematics/18152introductiontopartialdifferentialequationsfall2011/

UoM  Complex Analysis http://www.maths.manchester.ac.uk/~cwalkden/complexanalysis/complexanalysis.html

MIT  Fourier Analysis http://ocw.mit.edu/courses/mathematics/18103fourieranalysisfall2013/
If there is any input/advice anyone could give me, as to what I could add to bring this closer to a 'real' degree I would be very grateful.
1 points • sidXsid
Something slightly different, but I really enjoyed this one too
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2 points • Sarcuss
Yes, these are more applied statistics courses. If you want to delve deeply in the math, I think you would be well served with Mathematical Biostatistics part 1 and Part 2 or a textbook such as Mathematical Statistics with Applications by Wackerly et al.
1 points • gma617
I've considered it and I do think it would be fulfilling and lucrative potentially. But I don't have the baseline coursework from my undergrad (no biology, just standard stats). I did take a MOOC biostatistics course (https://www.coursera.org/learn/biostatistics) and I'm currently taking a python machine learning course (https://emeritus.org/universitycoursesonline/appliedmachinelearning/) so maybe with this helps my chances of being accepted into a masters program. Still feels like a long shot. What do you think the highestpaying career paths in bioinformatics would be? Wall Street can always just hire BME or Quantitative Finance PHDs, and it's not the time to enter equity research. Salary ranges I'm seeing for bioinformatics scientist are quite low, and that job would not utilize my peoplefacing skills developed in consulting. I must be overlooking something...
2 points • alejo_sc
I did a lot of online review to prepare me for my Masters program, mostly through Coursera. They have a lot of great Biostats and Data Science courses:
Basic Statistics  University of Amsterdam
Epidemiology: The Basic Science of Public Health  University of North Carolina  Chapel Hill
Statistical Reasoning for Public Health  Johns Hopkins University
Mathematical Biostatistics Bootcamp Johns Hopkins University
I don't know of any resources for developing your SPSS skills, but Datacamp helped me a ton with learning R.
1 points • MathIsNotBeautiful
The below MOOC's might be worth checking out.
Coursera:
EdX:
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Also, if you're willing to do some selfstudy, there are several lecture series available on YouTube that might be of interest to you. Below are a couple of examples.
YouTube:
 MATH 481 Mathematical Statistics I taught by Greg Morrow at the University of Colorado  Colorado Springs
 Undergraduate courses on both probability and mathematical statistics taught by Christina Knudson at the University of St. Thomas