Boot Camp in Quantitative Methods

August 2020

MATLAB Programming Style Guidelines

This document by Richard Johnson can help you produce code that is more likely to be correct, understandable, sharable and maintainable. (zip file)

MATLAB Good Programming Practices

Writing code that is easy to read and maintain is an essential skill for a good programmer. Read the document here (pdf)

MATLAB cross-references to other languages

For statistical calls, Hiebeler's guide is good. And this one by Gundersen covers both 'R' and Python.


Matlab: A Practical Introduction to Programming and Problem Solving by Stormy Attaway.

Other MATLAB books for specific topics are cataloged on the MathWorks web site.

Statistics Blogs

A fascinating and educational stats blog, Data Colada, by Uri Simonsohn and colleagues.

Andrew Gelman's stats blog.

How to Share Data with a Statistician

This excellent guide by Jeffrey Leek from Johns Hopkins Bloomberg School of Public Health explains how best to prepare, process and annotate raw data before sending it to a statistician for analysis. Also helpful if you do your own data analysis!

Statistics course at MIT

Class notes and other useful information from Introduction to Probability and Statistics Spring 2014 by Drs. Jeremy Orloff and Jonathan Bloom

Literature on Bootstrapping

The classic: An Introduction to the Bootstrap by Bradley Efron and Robert Tibshirani.

Image Processing

HMS has an excellent core facility that specializes in MATLAB based image analysis: Image and Data Analysis Core.

Version control and code sharing

A helpful introduction on how to use git and github to keep track of, manage, and share code can be found here.

The Scriptome - Protocols for Manipulating Biological Data

The scriptome is a set of tools built by the Center for Systems Biology that filter, format, and merge data in tabular or common biological formats. Check the website here

Jon Shlens tutorial on PCA

Jon Shlens 2003

O2 High Performance Computing Cluster

Request an account on O2 here