April 2013

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Data Management in Stata

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

 
 
 
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Regression in Stata

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
4/12/2013 9:00am to 11:00am
 
Graphing in Stata

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
4/12/2013 11:00am to 1:00pm
 
 
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Introduction to R

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
4/26/2013 9:00am to 12:00pm
 
 
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