What you will learn in Biostatistics in Public Health Specialization Course
Calculate summary statistics from public health and biomedical data.
Interpret written and visual presentations of statistical data.
- Evaluate and interpret results of various regression methods.
- Choose the most appropriate statistical method to answer your research question.
Program Overview
Summary Statistics in Public Health
⏱️15 hours
Calculate continuous data measures.
Interpret data visualizations.
Analyze binary data.
Analyze time-to-event data.
Hypothesis Testing in Public Health
⏱️19 hours
Use statistical methods to analyze sampling distributions.
Estimate and interpret 95% confidence intervals for single samples and two populations.
Estimate and interpret p-values for hypothesis testing.
Simple Regression Analysis in Public Health
⏱️ 15 hours
Practice simple regression methods to determine relationships between an outcome and a predictor.
Recognize confounding in statistical analysis.
Perform estimate adjustments.
Multiple Regression Analysis in Public Health
⏱️14 hours
Practice multiple regression methods to determine relationships between an outcome and multiple predictors.
Use the spline approach for non-linear relationships with continuous predictors.
Perform calculations with multiple predictor variables.
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Job Outlook
Professionals trained in biostatistics are in demand across various fields, including public health, healthcare, and research. Key skills include:
Knowledge of statistical methods and their application in public health.
Ability to analyze and interpret biomedical data.
Proficiency in statistical software and data visualization tools.
Specification: Biostatistics in Public Health Specialization
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FAQs
- It helps analyze patterns in health-related data.
- Used to evaluate the effectiveness of treatments and interventions.
- Supports public health policies by providing scientific evidence.
- Essential for understanding disease trends and improving population health.
- A general understanding of high school-level math is enough.
- No prior experience in advanced statistics is required.
- The course explains concepts step by step with real-world examples.
- Visualizations and health datasets make the learning more practical.
- Basics of probability, distributions, and sampling.
- Statistical inference and hypothesis testing.
- Regression analysis for health data.
- Study design and data interpretation in public health research.
- Analyze public health surveys and clinical trial data.
- Interpret findings to inform health decisions and interventions.
- Support research projects in healthcare and epidemiology.
- Communicate statistical results to health professionals and policymakers.
- Public health students and professionals.
- Healthcare workers looking to expand research skills.
- Policy analysts working with health data.
- Anyone interested in applying statistics to health-related problems.
