This episode reviews the core principles of surgical research design and statistical analysis, focusing on how to build, interpret, and critique clinical studies. Topics include PICOS, a priori versus post-hoc analysis, hierarchy of evidence, clinical trial phases, efficacy versus effectiveness, sampling methods, selection bias, generalizability, hypothesis testing, type I and type II errors, statistical power, p-values, confidence intervals, and the difference between statistical and clinical significance. The episode also covers variable types, normal versus skewed data, mean versus median, standard deviation versus interquartile range, parametric and non-parametric testing, t-tests, paired t-tests, ANOVA, post-hoc tests, Chi-square, Fisher’s exact test, confounders, mediators, moderators, Table 1 interpretation, and the overadjustment trap. Part of Dr. Lara’s Plastic Surgery Compendium — a high-yield audio reference for plastic surgery trainees and surgeons. Disclaimer This podcast is intended for educational purposes only and is designed for medical students, residents, fellows, and practicing healthcare professionals. It is not intended to provide medical advice, diagnosis, or treatment for any individual patient. The content presented reflects general surgical principles and should not be used as a substitute for formal medical training, clinical judgment, or consultation with qualified healthcare professionals. Listening to this podcast does not establish a physician–patient relationship. SEO / Topic Keywords surgical research, research design, statistical analysis, evidence-based surgery, evidence-based medicine, plastic surgery research, clinical research, PICOS, PICO framework, a priori analysis, post-hoc analysis, data dredging, hierarchy of evidence, levels of evidence, expert opinion, case report, case series, case-control study, cohort study, randomized controlled trial, RCT, clinical trial phases, phase one trial, phase two trial, phase three trial, phase four trial, efficacy, effectiveness, sampling methods, simple random sampling, systematic sampling, stratified sampling, block sampling, convenience sampling, selection bias, generalizability, hypothesis testing, null hypothesis, alternative hypothesis, type I error, type II error, false positive, false negative, statistical power, beta error, p-value, confidence interval, odds ratio, relative risk, statistical significance, clinical significance, continuous variables, discrete variables, categorical variables, dichotomous variables, nominal variables, ordinal variables, normal distribution, skewed data, mean, median, standard deviation, interquartile range, parametric testing, non-parametric testing, t-test, paired t-test, ANOVA, Tukey test, Dunnett test, Chi-square test, Fisher exact test, confounder, mediator, moderator, Table 1, overadjustment bias
