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[REG-09] Biostatistics, Research Methodology, Pharmacoepidemiology & Evidence-Based Medicine (EBM)
REG-09 • 10. Clinical & Hospital PharmacyLearning Objectives
Select parametric (Student's t-test, ANOVA, Pearson r) vs non-parametric (Mann–Whitney U, Wilcoxon, Kruskal–Wallis, Chi-square χ²) statistical tests.; Calculate Relative Risk (RR), Odds Ratio (OR), Absolute Risk Reduction (ARR), and **Number Needed to Treat (NNT = 1 / ARR)**.; Distinguish Type I error (α, false positive) from Type II error (β, false negative; Statistical Power = 1 - β) and hierarchy of clinical evidence.
Chapter Overview & Core Explanation
Biostatistics and pharmacoepidemiology give pharmacists the mathematical tools to judge whether a new medicine truly saves lives in a clinical trial or whether an apparent difference happened merely by chance.
Key Exam & Clinical Takeaways
- Rejecting a true null hypothesis (H0) is a **Type I (α) False-Positive Error** (conventionally set at α = 0.05), whereas failing to reject a false null hypothesis is a **Type II (β) False-Negative Error** (Power = 1 - β, typically ≥ 80%).
- Number Needed to Treat (NNT) is the reciprocal of Absolute Risk Reduction (NNT = 1 / ARR), NOT Relative Risk Reduction.