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Topic 3.5 of Data Collection and Analysis Methods

Hypothesis Formulation and Testing

Null and alternative hypotheses, significance level and p-value, Type I and Type II error, and why a test can reject a hypothesis but can never prove it true.

~35 min total·4 quadrants of structured content

By the end of this topic, you will

State the null and alternative hypothesis for a given research question
Explain the difference between failing to reject a null hypothesis and confirming it
Explain the Type I / Type II error tradeoff and connect it to tuning a detection threshold
Explain why effect size matters alongside a p-value, not instead of it

Quadrant 1 · e-Tutorial

Video lectures and walkthroughs

Quadrant 2 · e-Content

Articles and case studies

research-methodology

Hypothesis Formulation and Testing

A test never proves the null hypothesis true. It only finds enough evidence to reject it, or it doesn't. Getting that distinction right is what separates a defensible result from an overclaimed one.

13 min read

Quadrant 3 · Web Resources

Downloadable material and curated external links

Web resources coming soon.

Quadrant 4 · Self-Assessment

Test your knowledge — earn a certificate on first pass

Assessment coming soon.