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.
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.
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