Have you always wanted to learn a programming language, but not sure how to get started? This workshop teaches the basic grammar of the python programming language, a powerful but easy to use tool for getting more out of your computer. Little to no knowledge of python or programming is assumed. Instructor: Kareem Carr
This hands-on class will provide a comprehensive introduction to graphics in Stata. Topics for the class include graphing principles, descriptive graphs, linear regression, factor variables, and post-estimation graphs. This is an introductory workshop appropriate for those with only basic familiarity with Stata. Prerequisite: a general familiarity with Stata (such as taking the Introduction to Stata workshop).
This class will introduce common data management techniques in Stata. Topics covered include basic data manipulation commands such as: recoding variables, creating new variables, working with missing data, and generating variables based on complex selection criteria. Participants will be introduced to strategies for merging datasets (adding both variables and observations), and collapsing datasets. This workshop is intended for users who have an introductory level of knowledge of Stata software.
This class will provide a hands-on introduction to Stata. You will learn how to navigate Stata’s graphical user interface, create log files, and import data from a variety of software packages. We will also share tips for getting started with Stata including the creation and organization of do-files, examining descriptive statistics, and managing data and value labels. This workshop is designed for individuals who have little or no experience using Stata software.
Get an introduction to SAS, one of the more frequently used statistical packages in business. With hands-on exercises, explore SAS's many features and learn how to import and manage datasets and and run basic statistical analyses. This is an introductory workshop appropriate for those with little or no experience with SAS.
Learn strategies for locating numeric data for term papers, senior theses, dissertations, or other research purposes. Taught by a Data Librarian from the Harvard College Library Numeric Data Services, this course covers everything from quick look-up sources to micro-level datasets in the social sciences, including those found in the IQSS Dataverse Network. Undertake hands-on practice using Harvard e-resources in Economics, Government and Political Science, Sociology, and Health. Both sessions cover the same material
This workshop offers a crash course on graphics and regression models in R. Topics covered include multiple regression, model comparison, mixed-effects models, and the construction of graphical displays using the ggplot2 package. This is an intermediate workshop appropriate for those already familiar with R.
This accelerated introduction will help you quickly get up to speed with the R statistical computing language. We will introduce the basics of the R language syntax, data import and management, package installation, and basic programming concepts including functions, classes and methods, iteration, and debugging. No prior R knowledge is required, but previous experience statistical or technical computing (e.g., Matlab, SAS, Stata, Python, and of course R) will be helpful.
Interested in using Twitter for academic research? Using R and Python, we will learn how to use the Twitter API and other tools to gather tweets, social networks and other available data and investigate a framework for analyzing it. Prerequisites: basic programming techniques (you can write a for loop).
In this workshop, we will provide a hands-on introduction to Matlab, including basic programming concepts such as data structures, functions and loops, as well as applicationsof these concepts to presenting stimuli and reading in data from external tools such as Qualtrics.
Our team of consultants can run trainings, give presentations to groups or hold office hours on site. If you have ideas for ways we can help your research, please get in touch: email@example.com