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Statistical Methods in Public Health I

1st term
4 credits
Academic Year:
2022 - 2023
Instruction Method:
Asynchronous Online with Some Synchronous Online
Lab Times:
  • Monday,  8:30 - 9:50am (01)
  • Tuesday,  8:30 - 9:50am (02)
  • Wednesday,  8:30 - 9:50am (03)
  • Thursday,  8:30 - 9:50am (04)
  • Friday,  8:30 - 9:50am (05)
  • Monday,  1:30 - 2:50pm (06)
  • Tuesday,  1:30 - 2:50pm (07)
  • Wednesday,  1:30 - 2:50pm (08)
  • Thursday,  1:30 - 2:50pm (09)
  • Friday,  1:30 - 2:50pm (10)
  • Monday,  3:30 - 4:50pm (11)
  • Tuesday,  3:30 - 4:50pm (12)
  • Monday,  3:30 - 4:50pm (13)
  • Monday,  3:30 - 4:50pm (14)
  • Monday,  3:30 - 4:50pm (15)
  • Note:
    Student also must register for one Lab (140.921.xx). Students choose a day/time/format for a weekly Lab 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
Undergrads Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructors:
Marie Diener-West

Introduction to Online Learning is required prior to participating in any of the School's Internet-based courses.


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
Methods of Assessment:

This course is evaluated as follows:

  • 20% Assessments
  • 10% Quizzes
  • 70% Exam(s)

Instructor Consent:

Consent required for some students

Consent Note:

Consent Required for non-PH students

For consent, contact:

Special Comments:

Lectures are asynchronous and pre-recorded. LiveTalks: Synchronous online every Tuesday from 7-8:30 pm ET. Each student registers for one Lab Section 140.921.xx (02,05,09 and 13 are Stata online labs; 03,07,10,12 and 14 are Stata onsite labs; 01 and 06 are R online labs; 04,08,11 and 15 are R onsite labs).