Hypothesis Testing in Public Health

Johns Hopkins develops the reasoning behind estimates and statistical tests using population comparisons. Confidence intervals lead into tests for means, proportions and incidence rates. It suits learners ready to connect the mechanics of a test with what the result can and cannot say.

What you will learn

• Explain sampling distributions and standard errors.
• Interpret confidence intervals for population measures.
• Compare statistical tests for two-group questions.

Who this suits

Learners with basic algebra, including logarithms and the equation of a line, following the course’s recommended preparation.

Before you enroll

This is education about populations and evidence, rather than individual treatment advice. Check the dates and setting of any statistics or policy examples. A completion certificate does not replace a professional public-health or clinical qualification.

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Put it into practice

Compare two fictional population samples and explain the estimated difference, uncertainty and assumptions before writing a conclusion.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

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