"The goal of this course is to (1) identify and explain basic statistical principles that are widely applicable to the analysis of neuroscience and behavioral data and (2) show how these principles can be translated into practice using MATLAB as the programming environment. Topics will include probability distributions, error bars and confidence intervals, statistical significance, regression, classification, correlation, linear and nonlinear models, cross-validation, bootstrapping, model selection, and randomization methods. We will focus on nonparametric and computational approaches to statistical problems, as opposed to classical statistical approaches involving parametric assumptions and analytic solutions. This course is intended for graduate students or postdocs who would like to gain a better understanding of statistical principles and/or learn how to program in MATLAB. Auditors are welcome."

syllabi
statistics
data
analysis
matlab
october 2016 by tsuomela

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