Social Science Data Services
Finding and Managing Data for Research

Data services > Workshops

See also: Data Access, Support for Statistical Software, Tutorials.

IAP 2012 Workshops

Finding and Managing Data
Statistical Software

Preregister for all workshops at: http://mit.libcal.com//.

Finding and Managing Data

1. Finding Research Datasets: ICPSR and the Harvard-MIT Data Center

Need data to answer a research question? Interested in analyzing raw datasets with micro-level records about individual respondents? This hands-on workshop will familiarize you with the resources of the Inter-university Consortium for Political and Social Research (ICPSR) and the Harvard-MIT Data Center, which provide access to datasets in the social sciences and related fields. Topics will include the structure of data files, finding and downloading datasets, and understanding data documentation.

When: Friday, January 20, 2012, 10-11:30am

Where: 14N-132. Space is limited: pre-register online

2. Managing Research Data 101

For researchers struggling to manage their data, this workshop provides basic strategies for:

• best practices for retention and archiving
• effective directory structures and naming conventions
• good file formats for long-term access
• data security and backup options
• metadata, tagging, and citation
• complying with data management plan requirements

When: Tuesday, January 17th, 2012, 1-2pm

Where: 14N-132. Space is limited: pre-register online

3. Public Opinion Data Resources

Interested in studying public opinion in the U.S. and other countries? Want to gauge how the electorate stands on issues in advance of the 2012 election? This workshop will teach you how to find data from public opinion polls, both summary statistics and individual response-level data files that you can analyze yourself. Covers the Roper Center for Public Opinion Research and other resources on topics such as government, the economy, and much more.

When: Wednesday, January 25th, 10-11am

Where: 14N-132. Space is limited: pre-register online

Statistical Software

Looking to gain skills in working with statistical analysis software packages?  The following classes will be taught by the Harvard-MIT Data Center (HMDC) Statistical Trainer during IAP.  Note: there will be time at the end of each session for individual assistance, so feel free to bring your research questions. Materials from the workshops are available at: http://people.iq.harvard.edu/~izahn/mit2012/.

Where: All workshops held in 1-115.

1. Introduction to Stata

This workshop is designed for individuals who have little or no experience using Stata software. 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.

When: Tuesday, January 24th, 9am-12pm; Space is limited: pre-register online

2. Data Management 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. Prerequisite: a general familiarity with Stata (such as taking the Intro. workshop).

When: Friday, January 27th, 1-3pm; Space is limited: pre-register online

3. Regression Using Stata

This hands-on class will provide a comprehensive introduction to estimating the linear regression model using ordinary least squares in Stata. Topics covered include: univariate and multiple regression, dummy variables, interaction effects, hypothesis tests, assumption testing, and strategies for organizing model testing. Prerequisites: General familiarity with Stata, including importing and managing datasets and data exploration (such as taking the Intro. workshop); knowledge of the linear regression model and ordinary least squares estimation.

When: Friday, February 3rd, 10am-12pm; Space is limited: pre-register online

4. Graphics in Stata

Graphs are a powerful and memorable means of communicating quantitative information. 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. Prerequisite: a general familiarity with Stata (such as taking the Intro. workshop).

When: Friday, February 3rd, 1-3pm; Space is limited: pre-register online

5. Introduction to SAS

This course is intended for individuals with little to no experience using SAS, a powerful statistical software package available on Athena.  With hands-on exercises, explore SAS's many features and learn how to import and manage your data in SAS. Novices welcome!

When: Friday, January 27th, 9am-12pm; Space is limited: pre-register online

6. Introduction to R

Get an introduction to R, the open-source system for statistical computation and graphics available on Athena. With hands-on exercises, learn how to import and manage datasets, create R objects, and generate figures. Novices welcome!

When: Tuesday, January 24th, 1-4pm; Space is limited: pre-register online

7. R and Statistics

This hands-on, advanced R course will demonstrate a variety of statistical procedures using the open-source statistical software program, R. Prerequisites: Familiarity with the following statistical processes (the course will teach how to run those processes in R):
- Introduction to using Zelig in R
- Regression models (linear, logistic, poisson, etc.)
- Multilevel modeling
- Multiple imputation
- Running analyses with multiply imputed datasets

When: Wednesday, February 1st, 9am-12pm; Space is limited: pre-register online

8. R Programming

This hands-on, advanced R course will guide users through a variety of programming functions in the open-source statistical software program, R. Programming skills in the following areas (the course will teach only how to run those processes in R):
- Blocks, loops, functions, if/then statements
- Objects and lists
- Timing and random variable generating functions
- Using C, C++, and Fortran functions
- Interactive batch use
- Debugging: traceback, debugger
- Memory and time profiling: Rprof, proftools, profr
- Using Parallelism: Rmpi, Snow, calling R from Python

When: Wednesday, February 1st, 1-4pm; Space is limited: pre-register online

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Can’t make these times? View the class materials at: http://people.iq.harvard.edu/~izahn/mit2012/ or attend these workshops at Harvard.

For alternatives, see:

• MIT users can attend Harvard-MIT Data Center Statistical Computing Classes; and
• for help in searching for data, contact Katherine McNeill, Social Science Data Services and Economics Librarian, mcneillh@mit.edu.

This page was last updated on Wednesday, 18-Apr-2012 16:56:57 EDT