Biostatistics in Public Health

Johns Hopkins University

This specialization in Biostatistics in Public Health is designed for public health and healthcare professionals, researchers, data analysts, and social workers. It provides a concepts-centric primer on biostatistics, equipping learners with essential statistical skills for interpreting and analyzing data in public health, medicine, biological science, and related fields. Upon completion, participants will have the ability to read and respond to the scientific literature, including the Methods and Results sections, as well as engage as part of a research team.

The course covers a range of key topics, including:

  • Calculation of summary statistics from public health and biomedical data
  • Interpretation of written and visual presentations of statistical data
  • Evaluation and interpretation of results of various regression methods
  • Selection of the most appropriate statistical method to answer research questions

Offered by Johns Hopkins University, this course enables learners to develop the necessary statistical skills to contribute effectively to research and evidence-based decision-making in public health and related fields.

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Biostatistics in Public Health
Course Modules

This course covers essential modules in biostatistics, including Summary Statistics in Public Health, Hypothesis Testing, Simple Regression Analysis, and Multiple Regression Analysis. Gain the skills to calculate, interpret, and analyze statistical data for effective research participation.

Summary Statistics in Public Health

This module focuses on calculating summary statistics from public health and biomedical data. Participants will learn to interpret data visualizations and analyze different data types, including continuous, binary, and time-to-event data.

Hypothesis Testing in Public Health

Explore hypothesis testing methods in public health, including the use of statistical methods to analyze sampling distribution, estimation and interpretation of confidence intervals for single and two populations, and interpretation of p values for hypothesis testing.

Simple Regression Analysis in Public Health

This module covers the practice of simple regression methods to determine relationships between an outcome and a predictor. Participants will also learn to recognize confounding in statistical analysis and perform estimate adjustments.

Multiple Regression Analysis in Public Health

Participants will practice multiple regression methods in this module to determine relationships between an outcome and multiple predictors. The Spline approach for non-linear relationships with continuous predictors and calculations with multiple predictor variables will also be covered.

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