Research Methods

Introduction to Data Analysis and Interpretation

Summarize, visualize, and interpret health data using practical statistical and analytical methods for real research questions.

5 lessons 54 steps English Self-paced

Create free account View curriculum

Course overview

Turn raw data into clear, defensible conclusions.

Summarize, visualize, and interpret health data using practical statistical and analytical methods for real research questions.

Compare descriptive and inferential approaches

Distinguish how descriptive statistics summarize data versus how inferential methods and causal reasoning draw conclusions from it.

Match the method to the data

Select the right statistic, visualization, or regression approach based on your variable types, distribution, and research question.

Recognize pitfalls and confounders

Identify bias, confounding, skewed distributions, and other traps that can distort interpretation before they reach your conclusions.

Plan stronger analyses

Turn your data and objectives into a clear statistical analysis plan and a defensible, reproducible interpretation of results.

Learning path

Lessons are organized into short, completable steps so learners can make progress even during a busy clinical or research week.

Designed for completion

Short lessons

Clear steps make the course easier to finish alongside clinical and research duties.

Field-ready tools

Use course examples and checklists to apply learning in real research workflows.

Bilingual pathway

English and French course support helps teams learn across language contexts.