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.
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 course will guide you through a variety of programming functions in the open-source statistical software program, R. It is intended for those already comfortable with using R for data analysis who wish to move on to writing their own functions. To the extent possible this workshop uses real-world examples. Concepts will be introduced as they are needed for a realistic analysis task. In the course of working through a realistic project we will lean about interacting with web services, regular expressions, iteration, functions, control flow and more.
Prerequisite: basic familiarity with R, such as acquired from an introductory R workshop.
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.