This nine-part series introduces participants to
diverse types and sources of data as well as ways to interpret and present data
for maximum effectiveness. Participants will explore data and statistics used
to make decisions, and answers to questions such as, How are these data
collected? What do these numbers mean for my community’s health? and How
can I best share these data with my stakeholders?
Part 1: Data Sources
Part 2: Types of Data
Part 3: Descriptive Statistics
Part 4: Inferential Statistics
Part 5: Epidemiologic Concepts
Part 6: Interpreting Data
Part 7: Presenting Data
Part 8: What Software to Use
Part 9: Conclusions
**Instructions to access the course will be provided after you register.**
Jeanine Buchanich, PhD, MEd, is a Research Associate Professor of Biostatistics at the University of Pittsburgh School of Public Health and serves as the Deputy Director for the Center for Occupational Biostatistics and Epidemiology. Her work includes improving the communication of statistical and scientific information to the general public and to stakeholders.
This course is appropriate for public health and clinical practitioners seeking an introduction to data analytics.
This course is presented through the Vimeo Internet-based platform. A computer with high-speed internet connection and the ability to download and run this platform is required.
This training was originally presented in March to April 2019.
For more information about this course or assistance with registration, contact firstname.lastname@example.org.
This case study, which illustrates how public health
informatics can make a real world impact, follows the development of a public
health informatics tool from the identification of the problem to the creation
of an online app. It focuses on the purposes of a Heat Vulnerability Index and
explores how it can be used to assist our communities.
At the conclusion of this case study, participants will be able to:
- describe one way in which public health informatics can make a real-world impact.
to access the resource will be provided after you register.**
This animation is appropriate for all public health professionals.
This self-guided animation illustrates how public health informatics can
make a real-world impact by exploring how a computational model created by
scientists at the University of Pittsburgh influenced the enactment of
California’s current vaccination policy. The model, A Framework for
Reconstructing Epidemic Dynamics (FRED), simulates the spread of an
epidemic in two populations: one with herd immunity as a result of high levels
of vaccination and one without herd immunity as a result of low levels of
vaccination. After viewing FRED, policymakers voted in favor of a new policy to
increase vaccinations among school-aged children.
to access the course will be provided after you register.**
At the conclusion of this animation, participants will be able to:
- describe one way in which public health informatics can make a real-world impact; and
- define herd immunity.
This presentation is appropriate for all public health practitioners.
This course is appropriate for those with no or basic levels of experience with informatics.
Length: 15 minutes
A computer with high-speed internet connection is required to view this course.
For more information about this course or for assistance with registration, contact email@example.com.
This course was created in April 2022.
Each term is defined and examples are available when appropriate. Additional resources have been provided so that you can pursue further study of each topic.
**Instructions to access the resource will be provided after you register.**
For more information, contact firstname.lastname@example.org.