Workshop Materials

We offer a series of data analysis and programming workshops to members of the Harvard and MIT communities. If you are a Harvard affiliate, you can register here to take these workshops. If you are a MIT affiliate, you should contact the MIT library for registration. If you are not a Harvard or MIT affiliate, or if your schedule does not permit you to attend these workshops, you can still use our workshop materials for self-study.

Python Introduction

Description

Materials for the "Python Introduction" workshop. This hands-on workshop introduces the basic elements of Python by working through an example of how to analyze text data. Python is a general purpose programming language commonly used for data cleaning, analysis, visualization, and other applications. Note that the focus of the workshop is on how to use Python rather than why you might want to use Python over other software. This workshop is appropriate for those with little or no prior experience with Python.

Materials and resources

Python Web Scraping

Description

Materials for the "Python Web Scraping" workshop. This hands-on workshop will introduce basic techniques for web-scraping using popular Python libraries. This is an intermediate-level, and somewhat challenging, workshop appropriate for those who have been using Python for at least a few months. You should be familar with all of the material in the Python Introduction workshop and have used these skills in your own projects to the point where you are comfortable with them.


Materials and resources

R Introduction

Description

Materials for the "R Introduction" workshop. This hands-on workshop will teach you how to use R to import and manipulate data, install and manage packages, conduct basic statistical analyses, and create common graphical displays. Note that the focus of the workshop is on how to use R rather than why you might want to use R over other software. This workshop is appropriate for those with little or no prior experience with R.

Materials and resources

R Regression models

Description

Materials for the "R Regression models" workshop. This hands-on workshop will demonstrate how to deploy a variety of statistical procedures using R, including multiple regression, modeling with categorical variables, as well as model diagnostics and comparison. Note that the focus of the workshop is on how to use R to fit models - we do not teach the theory behind the models and assume that you already have a solid background in statistical modeling and want to apply this in R. This is an intermediate-level workshop appropriate for those who have been using R for at least a few weeks. You should be familar with all of the material in the R Introduction workshop and have used these skills in your own projects.

Materials and resources

R graphics

Description

Materials for the "R graphics" workshop.This hands-on workshop provides an introduction to the popular ggplot2 R graphics package. It will cover how to create a wide variety of graphical displays in R, using techniques such as layering, mapping variables to aesthetics, working with scales, faceting, and themes. This is an intermediate-level workshop appropriate for those who have been using R for at least a few weeks. You should be familar with all of the material in the R Introduction workshop and have used these skills in your own projects. 

Materials and resources

R data wrangling

Description

Materials for the "R data wrangling" workshop. This hands-on workshop will prepare you for dealing with messy data by walking you through a real-life example. This is an intermediate-level workshop appropriate for those who have been using R for at least a few weeks. You should be familar with all of the material in the R Introduction workshop and have used these skills in your own projects.

Materials and resources

Stata Introduction

Description

Materials for the "Stata Introduction" workshop. This hands-on workshop provides an introduction to Stata, including how to import and manipulate data, as well as calculate descriptive statistics. This workshop is appropriate for those with little or no prior experience with Stata.

Materials and resources

Stata Data Management

Description

Materials for the "Stata Data Management" workshop. This hands-on workshop provides an overview of data management in Stata, including how to generate and replace variables, deal with missing values, work with variable types and convert variable types, as well as merge, append, and joining different data sets, and create summarized data sets. This workshop is appropriate for those who have some prior introductory experience with Stata. 

Materials and resources

Stata Regression Models

Description

Materials for the "Stata Regression Models" workshop. This hands-on workshop provides an overview of modeling in Stata, including how to fit models for continuous outcomes, for binary outcomes, how to export and save results, and how to obtain quantities of interest from a fitted model. Note that we assume you have the theoretical statistical background to understand the models covered in the workshop - we focus solely on how to implement these models in Stata. This workshop is appropriate for those with some prior introductory experience with Stata.

Materials and resources

Stata Graphics

Description

Materials for the "Stata Graphics" workshop. This hands-on workshop provides an overview of graphing in Stata, including how to produce various types of univariate (e.g., histograms) and bivariate (e.g., scatterplots) graphs. This workshop is appropriate for those with some prior introductory experience with Stata.

Materials and resources

Introduction to Programming

Description

Materials for the "Introduction to Programming for Researchers" workshop.

Materials and resources

Data Science Tools

Description

Materials for the "Data Science Tools" workshop. In this workshop we look at the kinds of tools that data scientists use (programming languages, statistics packages, version control, text editors and integrated development environments) and discuss the pros and cons of popular alternatives.

Materials and resources

SAS Introduction

Description

Materials for the "Data Science Tools" workshop. In this workshop we look at the kinds of tools that data scientists use (programming languages, statistics packages, version control, text editors and integrated development environments) and discuss the pros and cons of popular alternatives.

Materials and resources

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