📖 Course Overview
This course equips students with essential skills to transform public health data into actionable insights that support evidence-based decision-making. The curriculum blends fundamental statistical concepts, practical data management, and visualization techniques using accessible analytical tools. Participants will learn through hands-on exercises. By the end of the course, students will be able to manage, analyze, and interpret public health data, communicate findings effectively, and ensure analytical rigor and ethical standards across the entire data workflow.
🔑 Key Topics Covered
Types and sources of public health data, data structures, levels of measurement, introduction to analytical workflow
Data importation, labeling variables, handling missing values, ensuring consistency and reproducibility
Summarizing data using tables and graphs, measures of central tendency and dispersion, exploratory analysis
Creating clear visual outputs, using graphs, communicating trends and patterns effectively
t-tests, chi-square, ANOVA, correlation; understanding p-values and confidence intervals
Simple and multiple linear regression, logistic regression, interpretation of coefficients, prediction exercises
Time-series analysis, survival analysis, introduction to multilevel models
Interpreting analytical results, developing tables and figures for reports
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