Workshops

Introduction to R - ComputeFest 2013

Date: 

Wednesday, January 16, 2013 (All day)

This is an INTRODUCTION to R. We assume no/very little knowledge of R!

Learning objectives:

  • Install and load R packages
  • Find package and function documentation
  • Load external data into R
  • Create and query vectors, matrices, and data frames
  • Compute descriptive statistics and regression models
  • Construct basic graphical displays

Mining Twitter Data

Date: 

Wednesday, January 23, 2013 (All day)

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).

Introduction to SAS

Date: 

Friday, March 15, 2013, 9:00am to 12:00pm

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.

Spring 2013 Schedule

Fri, 03/15/2013

Graphing in Stata

Date: 

Friday, April 12, 2013, 11:00am to 1:00pm

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).

Spring 2013 Schedule

Fri, 04/12/2013: 11am-1pm

Regression in Stata

Date: 

Friday, April 12, 2013, 9:00am to 11:00am

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.

Spring 2013 Schedule

Fri, 04/12/2013: 9am-11am

Data Management in Stata

Date: 

Friday, April 5, 2013 (All day)

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.

Spring 2013 Schedule

Fri, 04/05/2013: 9am-Noon

Introduction to Stata

Date: 

Friday, March 29, 2013, 10:00am to 1:00pm

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.

Spring 2013 Schedule

Fri, 02/08/2013: 10am-1pm
Fri, 03/29/2013: 10am-1pm

Introduction to R Graphics with ggplot2

Date: 

Friday, May 17, 2013, 9:00am to 12:00pm

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.

Spring 2013 Schedule

Fri, 03/08/2013: 9am-Noon
Fri, 05/10/2013: 9am-Noon

R Programming

Date: 

Friday, May 3, 2013, 9:00am to 12:00pm

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.

Spring 2013 Schedule

R Regression Models

Date: 

Friday, May 10, 2013, 9:00am to 12:00pm

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.

Introduction to R

Date: 

Friday, April 26, 2013, 9:00am to 12:00pm

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.

Spring 2013 Schedule

Fri, 02/15/2013: 9am-12pm
Fri, 04/19/2013: 9am-12pm

Introduction to Numeric Data Resources

Date: 

Friday, March 29, 2013, 9:00am to 10:00am

Introduction to Numeric Data Resources

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.