Hypothesis Test Course
Dive into hypothesis testing using authentic clinical survey data. Master data cleaning, assumption validation, robust statistical testing, and transforming results into compelling, executive-friendly insights that support data-driven decisions with assurance. Build proficiency in R, Python, and Excel for reproducible workflows tailored to clinical environments.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This course provides a rapid, hands-on guide to conducting reliable hypothesis tests on clinical survey data and confidently presenting findings. Participants will learn to prepare and examine datasets, validate key assumptions, select suitable statistical tests, and use advanced techniques when standard conditions aren't met. Gain skills in automating reports, articulating precise conclusions, and producing repeatable, thoroughly documented analyses trusted by decision-makers.
Elevify advantages
Develop skills
- Conduct clinical hypothesis tests: perform t-tests, confidence intervals, and nonparametric analyses efficiently.
- Diagnose assumptions: assess normality, variance homogeneity, clustering, and test robustness.
- Control for confounders: implement ANCOVA, regression models, and stratified analyses.
- Develop reproducible pipelines: create R, Python, and Excel workflows for survey data processing.
- Craft executive reports: convert statistical results into clear visuals and summaries for managers.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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