Cross-Disciplinary Fellowships (XDF)

Physics, Mathematics & Statistics

Physics, Mathematics & Statistics resources

Free online Physics courses

A good collection of Physics courses from “Open Culture”.

Website: http://www.openculture.com/physics_free_courses

Introduction to Probability and Statistics

This course provides an elementary introduction to probability and statistics with applications. Topics include: basic combinatorics, random variables, probability distributions, Bayesian inference, hypothesis testing, confidence intervals, and linear regression.

Website: https://ocw.mit.edu/courses/mathematics/18-05-introduction-to-probability-and-statistics-spring-2014/

Probability and Statistics

The Probability and Statistics course contains four main units (Exploratory Data Analysis, Producing Data, Probability, Inference) that have several sections within each unit. It is designed to be equivalent to one semester of a college statistics course.

Website: https://online.stanford.edu/courses/gse-yprobstat-probability-and-statistics

Modern Statistics for Modern Biology

The aim of this book by Susan Holmes, and Wolfgang Huber is to enable scientists working in biological research to quickly learn many of the important ideas and methods that they need to make the best of their experiments and of other available data.

Website: http://web.stanford.edu/class/bios221/book/introduction.html#introduction

Statistical Thinking for the 21st Century

This book by Russell A. Poldrack describes the approaches that are increasingly used in real statistical practice in the 21st century. Themethods described take advantage of today’s increased computing power to solve statistical problems in ways that go far beyond the more standard methods that are usually taught in the undergraduate statistics courses.

Website: http://thinkstats.org/

Seeing Theory

A visual introduction to probability and statistics

Website: https://students.brown.edu/seeing-theory/

Statistical Thinking and Data Analysis

This course is an introduction to statistical data analysis. Topics are chosen from applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and nonparametric statistics.

Website: https://ocw.mit.edu/courses/sloan-school-of-management/15-075j-statistical-thinking-and-data-analysis-fall-2011/

Statistics for Applications

This course offers an in-depth theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathematics in the research and development of efficient statistical methods.

Website: https://ocw.mit.edu/courses/mathematics/18-650-statistics-for-applications-fall-2016/

Selective Inference and False Discovery Rate I

Interesting lecture on multiple hypothesis testing.

Website: https://www.youtube.com/watch?v=oONHlua2gBY

Statistics and R

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

Website: https://www.edx.org/course/statistics-r-harvardx-ph525-1x-1

Explore Statistics with R

Learn basic statistics in a practical, experimental way, through statistical programming with R, using examples from the health sciences.

Website: https://www.edx.org/course/explore-statistics-r-kix-kiexplorx-0

Introduction to Statistical Methods for Gene Mapping

This data course is a primer to statistical genetics and covers an approach called linkage disequilibrium mapping, which analyses non-familial data and has been successfully used to identify genetic variants associated with common and complex genetic traits.

Website: https://www.edx.org/course/introduction-to-statistical-methods-for-gene-mapping

Introduction to Mathematical Thinking

The goal of the course is to help you develop a valuable mental ability – a powerful mathematical way of thinking that our ancestors have developed over three thousand years.

Website: https://online.stanford.edu/courses/hstar-y0001-introduction-mathematical-thinking

Applications of Linear Algebra Part 1

Learn to use linear algebra in computer graphics by making images disappear in an animation or creating a mosaic or fractal and in data mining to measure similarities between movies, songs, or friends.

Website: https://www.edx.org/course/applications-linear-algebra-part-1-davidsonx-d003x-1

Applications of Linear Algebra Part 2

Explore applications of linear algebra in the field of data mining by learning fundamentals of search engines, clustering movies into genres and of computer graphics by posterizing an image.

Website: https://www.edx.org/course/applications-linear-algebra-part-2-davidsonx-d003x-2