This introduction to the popular ggplot2 R graphics package will show you how to create a wide variety of graphical displays in R. Topics covered included aesthetic mapping and scales, faceting, and themes. This is an intermediate level workshop appropriate for those already familiar with R. Participants should be familiar with importing and saving data, data types (e.g., numeric, factor, character), and manipulating data.frames in R.
This hands-on, intermediate R course will demonstrate a variety of statistical procedures using the open-source statistical software program, R. Topics covered include multiple regression, multilevel models, and multiple imputation. We expect that users enrolled in this course are already familiar with the statistical processes that we cover and are interested in learning how to run these procedures in R. Prerequisite: Basic familiarity with R, such acquired through an introductory R workshop.
This hands-on, intermediate R course will guide users through a variety of programming functions in the open-source statistical software program, R. This workshop covers blocks, loops, program flow, functions,S3 classes and methods, and debugging in R. This workshop is intended for those already comfortable with using R for data analysis who wish to move on to writing their own functions. Prerequisite: basic familiarity with R, such as acquired from an introductory R workshop.
Get an introduction to R, the open-source system for statistical computation and graphics. With hands-on exercises, learn how to import and manage datasets, create R objects, install and load R packages, conduct basic statistical analyses, and create common graphical displays. This workshop is appropriate for those with little or no prior experience with R.
This hands-on class will provide a comprehensive introduction to graphics in Stata. Topics for the class include graphing principles, descriptive graphs, and post-estimation graphs. This is an introductory workshop appropriate for those with little experience with graphics in Stata. Prerequisite: a general familiarity with Stata (such as taking the Introduction to Stata workshop).
This hands-on class provides a comprehensive introduction to estimating the linear regression model using ordinary least squares in Stata. Topics for the class include multiple regression, dummy variables, interaction effects, hypothesis tests, and model diagnostics. Prerequisites include a general familiarity with Stata, including importing and managing datasets and data exploration, the linear regression model, and the ordinary least squares estimation.
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.
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.
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.
See a workshop you'd like to take? Sign up by e-mailing: dataclass@help.hmdc.harvard.edu (please include your name and Harvard or MIT affiliation)
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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: support@help.hmdc.harvard.edu
