Biostatistics for the MCAT

The MCAT doesn't ask you to compute heavy statistics, but it constantly asks you to interpret them from figures and tables. Know what each measure means and when it's being misused.

Describing data

• Mean is pulled toward outliers; median is robust. In a right-skewed distribution, mean > median.
• Standard deviation measures spread; standard error of the mean (SEM = SD/√n) measures precision of the estimate and shrinks with sample size.
• A normal distribution has ~68% of values within 1 SD, ~95% within 2 SD, ~99.7% within 3 SD.

Inference

• A p-value is the probability of observing data this extreme if the null hypothesis were true. p < 0.05 is the conventional threshold; it is not the probability the hypothesis is true.
• Type I error (α) = false positive (reject a true null); Type II error (β) = false negative; power = 1 − β rises with larger sample size and effect size.
• A 95% confidence interval that excludes the null value (0 for a difference, 1 for a ratio) corresponds to p < 0.05. Wide intervals mean imprecise estimates.

Risk and association measures

• Relative risk (RR) = risk in exposed ÷ risk in unexposed (cohorts/RCTs).
• Odds ratio (OR) approximates RR for rare outcomes (case-control studies).
• RR/OR = 1 → no effect; > 1 → increased risk; < 1 → protective.
• Correlation (r) ranges −1 to +1 and measures linear association only — never assume causation from a correlation, and watch for confounding or non-linear relationships.

Statistical vs. clinical significance

A result can be statistically significant (p < 0.05) yet trivial in magnitude, especially with huge samples. MCAT answer choices often bait you into conflating the two — always check the effect size, not just the p-value.