Statistical Hypothesis Testing |P-Values, Errors & Significance Explained|USMLE Biostats Masterclass

Welcome to today’s high-yield USMLE biostatistics session on DoctorDC_Online, where we break down one of the most testable and foundational topics in medical statistics:
Statistical Hypothesis Testing — including null vs alternative hypotheses, type I & II errors, and P-values.

Whether you're interpreting clinical research or tackling tricky exam questions, this is a must-know concept for every medical student.

📌 What You’ll Learn in This Video:

🔍 Null vs Alternative Hypothesis

Null (H₀): No difference or effect

Alternative (H₁): There is a difference or effect

How we test H₀ and decide to reject or fail to reject it

📉 P-Value & Statistical Significance

What does P 0.05 really mean?

Interpreting statistical vs clinical significance

❗ Type I vs Type II Errors

Type I Error (α): False positive — reject H₀ when it's actually true

Type II Error (β): False negative — fail to reject H₀ when it's false

Power of a test = 1 − β

📊 Clinical Relevance & USMLE Vignettes

Vaccine studies, drug trials, and test comparisons

Real-world scenarios with exam-style MCQs

💡 Mnemonics, graphs, and memory tricks included!

🎓 Ideal For:

USMLE Step 1 & Step 2

PLAB, NLE, FMGE candidates

MBBS, BDS, MD students

Researchers and EBM learners

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