Applied Statistics for Health Research
For health professionals, researchers, and students who need to make sense of a health-research question, a table of study records, or a study result but are new to statistics. You leave able to turn that research question into a reviewable analysis: decide what the data can answer, choose a comparison that fits the study design, interpret an interval without claiming more than it supports, and report a result whose evidence path another person can follow. No statistics degree or programming experience is required.
Before you begin
This is a beginner-level course. No prior statistics or programming experience is required. The core path is no-code; optional technical practice with local files and guided Python or base R execution comes later.
Level 0 — Prepare to start the course is a private, non-blocking orientation. It helps you identify which basics about the research question, units, variables, dependence, summaries, and intervals to revisit before Module 1. It is not a lesson in local files or programming, and it collects nothing.
What you will learn
Thirteen topics build from framing a health-research question to interpreting and reporting an analysis for a research or service decision. Every topic includes a guided example and a no-code decision exercise. A wholly synthetic dataset, ready-to-copy Python and base R commands, and runnable labs are optional technical practice.
HEALTH.1 is the public preview. HEALTH.2–HEALTH.13 and HEALTH.AI are included in the complete course and require enrollment.
The course has four parts. First, turn the health question into a clear plan and check the data. Next, choose comparisons that match the groups and measurements. Then, read models and examine their assumptions. Finally, connect the question, decisions and results in a report another person can review.
Optional final practice
Try a new fictional case with fewer hints: write the analysis plan, find the data problems, choose one approach and explain its limits. This practice is outside the numbered course and is not required for completion.
REST-12 — From a health-analysis request to a clear analysis plan. Start with the health-analysis request and blank template; open the worked criteria only after recording your choice.
RWD-18 — Can these registry records answer this health-analysis question? Check whether the records suit the health-analysis question, codes changed over time, follow-up is incomplete, groups differ, or the result may not apply elsewhere.
Optional technical practice only: AURORA-30 is a fictional practice cohort with local files and a guided execution route. It is not part of the numbered course or needed to complete it.
Course access
First confirm that the learning path and study format fit what you need. The offer below includes the complete bilingual course and all optional practice resources.
Fourteen runnable Python and base R labs carry one synthetic health study from the research question to a reviewable evidence report. The complete EN/PT course, its capstone, and HEALTH.AI are included. This route uses the international USD offer.
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Individual self-study. No certificate, academic credit, live tutoring, statistical consulting, or clinical advice. Hotmart may offer Pix, boleto, and card depending on location; the checkout controls installments, taxes, conversion, and the final total.
Methods training with wholly synthetic data · not medical advice or authorization to conduct research