GUIDE TO INTRODUCTORY BIOSTATISTICS COURSE SEQUENCES
Biostatistics is the information science of public health. It is a way of reasoning and a methodology for addressing health questions using quantitative information. Our faculty and staff look forward to supporting your mastery of this important core discipline.
This page is designed to inform you about the four introductory Biostatistics course sequences available at Johns Hopkins. It will help you choose the one which will best enable you to achieve your learning objectives in preparation for your professional or scientific career in public health.
There are 4 introductory Biostatistics course sequences:
An option for completion of the biostatistics core course requirement for MPH students and selected MHS programs within other departments of the School.
Designed specifically for students within other departments of the School training to become a laboratory scientist.
Required by students in various master's and doctoral programs within other departments of the School and by MPH students in the Concentration in Epidemiological & Biostatistical Methods for Public Health and Clinical Research - Focus in Epidemiology.
Required by the master's programs within the Department of Biostatistics, MPH students in the Concentration in Epidemiological & Biostatistical Methods for Public Health and Clinical Research - Focus in Biostatistics, and other master's and doctoral students who will be conducting data analysis in epidemiologic or clinical research.
For Students of other Degree Programs
To find the most fitting sequence for you, try answering the following questions:
- Would you like an overview of biostatistical concepts and methods in two terms with minimal focus on computing and calculations and limited hands-on data analysis? If yes, then the 611-612 series is best suited to your needs.
- Are you seeking the ability to conduct yourself, or actively participate in, the design and data analysis for a public health practice or research program? If yes, then the 621-624 or 651-654 series is recommended. If not, then 611-612 or 615-616 would be suitable.
- If you seek design and data analysis skills, do you have a working knowledge of linear algebra and multivariate calculus from your previous training? If yes, then the 651-654 series would be appropriate. If not, then the 621-624 would be best.
Biostatistics 615-616 or Biostatistics 621-622: Which One Should I Take?
Biostatistics 615-616 and Biostatistics 621-622 cover largely the same material, although 615-616 concerns experiment data and so is most suited for laboratory scientists, while 621-622 concerns both experimental and observational studies. Both 615-616 and 621-622 provide sufficient preparation for Biostatistics 623-24.
Biostatistics 621-624 or Biostatistics 651-654: Which One Should I Take?
There are two introductory Biostatistics course sequences which emphasize data analysis skills, Biostatistics 621-624 and Biostatistics 651-654. They are both year-long courses (4 terms). Students typically take one or the other. A frequently asked question is, which one should I take?
The objectives of both courses are to introduce students to biostatistical methodology and to give students the skills to analyze data. In both sequences, you will learn many of the basic concepts including descriptive statistics, hypothesis testing, confidence intervals, p-values, sample size calculations, analysis of variance, linear regression, and logistic regression.
Biostatistics 621-624 teaches the tools and techniques of data analysis. Biostatistics 651-654 covers similar topics but explains statistical techniques in more depth and requires the students to have more advance mathematical skills.
It is required that students taking Biostatistics 651-654 have had a year of calculus and it is highly recommended that students have had a course in linear algebra. Both course sequences use computers and statistical analysis packages.
Frequently Asked Questions
Q: Who takes Biostatistics 651-654?
A: Students whose interests or main professional goals are to analyze data. Biostatistics graduate students are required to take it.
Q: I had calculus fifteen years ago and don't remember much. Could I still take Biostatistics 651-654?
A: Possibly. You would need to refresh your basic knowledge of derivatives and integrals. This could be done by investing time in initial self-study. Students in this situation have been successful in the course in the past but had to work somewhat harder.
Q: I never had linear algebra. Could I still take Biostatistics 651-654?
A: Linear algebra is used in the third and fourth terms of Biostatistics 651-654. Students need to have elementary knowledge of matrices. In the past, students who have put some time into acquiring this knowledge have been successful.
Q: Could I switch sequences in the middle of the school year?
A: No, not generally. The reason is that although the two sequences cover roughly similar topics, they are not taught in the same order.
Q: I want to learn regression and analysis of variance. Which course sequence should I take?
A: Both course sequences cover these topics, mostly in the third and fourth terms. Either sequence will give you a good working knowledge in order to apply these methods and understand the concepts. The main difference between the course sequences concerns the level of theoretical and mathematical development of the subjects matter.
Q: I'm still not sure I have the mathematical ability to handle 651-654. How can I tell?
A: You should be able to graph an exponential function; find values that minimize a function by setting the first derivatives equal to zero; perform an integration; perform algebraic manipulations; find the product of AB where A is a 2x3 matrix and B is a 3x2 matrix.
Still unsure? Check out the following resources for additional guidance:
- Problems to help you decide which sequence to take
- A test designed to help you decide whether you should enroll in the 651-B654 sequence
If you have further questions about which sequence is best for you, please contact Mary Joy Argo, Academic Administrator for the Department of Biostatistics.