Statistics for Brain and Cognitive Science
MIT OpenCourseWare offers this course covering the statistical tools needed to analyze experimental data and reason under uncertainty, aimed at students in brain and cognitive sciences. The curriculum is organized around three theories: probability (axioms, discrete and continuous models, the law of large numbers, and the Central Limit Theorem), statistics (estimation, likelihood, Bayesian methods, bootstrap and Monte Carlo methods, hypothesis testing, confidence intervals, experimental design, and goodness-of-fit), and the linear model (simple regression and analysis of variance). Theory, data analysis, and simulation studies receive equal weight throughout. Materials include MIT's standard OCW course content. As with other MIT OCW offerings, the course is free to audit with no certificate attached, and is best suited to students who already have some background in calculus and want a rigorous grounding in statistical reasoning.