Probability and Statistics - dtripathy10/datascience GitHub Wiki

Course Structure

• Introductory

• Theoretical Foundation

• Applied/Computation Foundation

• Design Foundation

• Application to Specific Domain

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Introductory

• Statistics 100: Introduction to Quantitative Methods for the Social Sciences and Humanities (Harvard)

• Statistics 101: Introduction to Quantitative Methods for Psychology and the Behavioral Sciences (harvard)

• Statistics 102: Statistics in Medicine and Modern Biology (harvard)

• Stats 104 (Harvard)

• Introductory Probability and Statistics for Business (UCBerkeley)

• Introductory Probability and Statistics for Business (UCBerkeley)

• Probability for Math Science (UCLA)

• Bayesian statistics made simple

Theoretical Foundation

• Probability and Statistics (NPTEL)

• Statistical Inference (NPTEL)

• Regression Analysis (NPTEL)

• Probability Theory and Applications (NPTEL)

• Stochastic Processes (NPTEL)

• Performance Evaluation of Computer Systems (NPTEL)

• Introduction to Probability- Stats-110 (Harvard)

• Introduction to Probability- Stats-110 Video (Harvard)

• Inference - Stats-111 (Harvard)

Applied/Computation Foundation

• Statistics 135 - Statistical Computing Software (harvard)

• CS 109 Data Science (harvard)

• Bayesian Data Analysis (Harvard)

• Probabilistic Graphical Models (Coursera)

• Statistics 202: Statistical Aspects of Data Mining (Google)

• Stochastic Hydrology (Time Series Analysis) (NPTEL)