Blog post: kisai: Course Review: PH207x Health in Numbers

Always a good feeling when wrapping up a book or a course. This is the first of my course reviews. Apparently, I take them as a hobby.

HarvardX: PH207x Health in Numbers: Quantitative Methods in Clinical & Public Health Research

Available on edX.

What it teaches:

Harvard's introductory course to biostatistics, which is statistics which focuses on public health models and analysis, and epidemiology, which is an investigation of the causes of diseases and conditions and their correlations. Epidemiology uses various case studies as frameworks to set up valid analysis for biostatistics.

Harvard taught these as two different courses, and this course is a fusion. The course also teaches how to use the

statistical software package Stata for assistance. It also introduces guest lecturers who lead the class in critiquing published case papers.

PH207x was planned as a 12 week course. If you already have a knowledge of statistics, you can probably fly through it. Most of the online homework questions refer to basic calculations and concepts.

Input[1]:

Basic fluency of algebra. Computer literacy.

Output:

Ability to understand basic statistics [2].

Ability to critique papers on epidemiological studies.

Ability to assist in biostatistics and epidemiology data analysis.

Ability to use basic Stata analysis.

Mixers:

Principles of Biostatistics (co-written by one of the lecturers, reviewed earlier in this blog)

Stata software package. Version 12 was used in the class, 14 was used for this review. Differences are mostly trivial[3].

Why You Should Take This Course:

First, if you have no prior knowledge of statistics, learning the subject is very informative. Statistics allows you to account for variability, probability, and prediction. Statistics gives you a set of tools which I find to be just as interesting and valuable as those from calculus. Second, you will be able to call bullshit on many claims given by people not just on statistics, but on health and nutrition as well. You'll know what makes a valid analysis and what to ask for evidence. Third, it was fun to see what a proper statistical program can do.

Do I recommend it?

Yes. The two instructors are well-versed and communicate their lectures very well. The textbook is lucid and not very formal, which is fine for applied mathematics. I had no problem understanding the material. For a very small investment: algebra and computer literacy, you get many useful rewards. Most especially, statistical analysis is a tool that isn't just limited to public health, but a wide amount of sciences, and I highly recommend learning it.

[1] What skills you need to properly process the course.

[2] The course will introduce linear and logistic regression, then recommend another course in regression.

[3] A calculator was relocated, and pseudo-random seeds will not be the same.
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