140.621.01
Statistical Methods in Public Health I

Location
East Baltimore
Term
1st Term
Department
Biostatistics
Credit(s)
4
Academic Year
2024 - 2025
Instruction Method
In-person
Class Time(s)
Tu, Th, 10:30 - 11:50am
Lab Note
After the course opens, students will sign up in the CoursePlus Sign-up Sheets for a weekly Lab Session with review of a structured Lab Exercise. - The format is either onsite or online (synchronous virtual via Zoom). - The data analysis tool is either Stata or R. Note: Students choosing R should have prior experience using a computer programming language (Python, C, R, MATLAB, etc.)
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Karen Bandeen-Roche
Marie Diener-West
Contact Name
Marie Diener-West
Frequency Schedule
Every Year
Description
Introduces the basic concepts and methods of statistics as applied to diverse problems in public health and medicine. Demonstrates methods of exploring, organizing, and presenting data, and introduces fundamentals of probability, including probability distributions and conditional probability, with applications to 2x2 tables. Presents the foundations of statistical inference, including concepts of population, sample parameter, and estimate; and approaches to inferences using the likelihood function, confidence intervals, and hypothesis tests. Introduces and employs the statistical computing package, STATA or R, to manipulate data and prepare students for remaining course work in this sequence.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Explain the role of quantitative methods and sciences in describing and assessing a population’s health
  2. Use statistical reasoning to formulate public health questions in quantitative terms within the scientific method
  3. Select quantitative data collection methods and variables appropriate for a given public health context
  4. Design and interpret graphical and tabular displays of statistical information, including stem and leaf plots, box plots, Q-Q plots and frequency tables.
  5. Distinguish and use appropriate probability models (binomial, Poisson, and Gaussian) to describe trends and random variation in public health data.
  6. Employ statistical methods for inference, including tests and confidence intervals, to draw public health inferences from data.
  7. Analyze quantitative data using either the Stata statistical analysis package or R package to construct tables and graphs and perform statistical methods for inference.
  8. Interpret results of data analysis for public health research, policy or practice
  9. Select the appropriate statistical method to evaluate the results of a public health program, policy or intervention
Methods of Assessment
This course is evaluated as follows:
  • 20% Assessments
  • 10% Quizzes
  • 70% Exam(s)
Enrollment Restriction
For onsite BSPH students or SON PhD students only. All other students may enroll in section 140.621.81 of this course.
Instructor Consent
Consent required for some students
Consent Note
Consent required for non-BSPH students. For consent, contact mdiener@jhu.edu
Consent Contact
mdiener@jhsph.edu
Special Comments

Restricted to 350 students. Lectures are synchronous onsite. After the term starts and the course opens, each student signs up in CoursePlus for one 80-minute onsite Lab Session.