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Finding Data  

This is a guide for finding demographic, economic, social, health, and environmental data sets that you can analyze, visualize, and map.
Last Updated: May 2, 2014 URL: http://libguides.gc.cuny.edu/findingdata Print Guide RSS Updates

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Searching for data

When searching for data, ask yourself these questions...

Who has an interest in collecting this data?

  • If federal/state/local agencies or non-governmental organizations, try locating their website and looking for a section on research or data.
  • If social science researchers, try searching ICPSR.

What literature has been written that might reference this data?

  • Search a library database or Google Scholar to find articles that may have used the data you're looking for. Then, consult their bibliographies for the specific name of the data set and who collected it.
 

Evaluating data

Is the data...

  • From a reliable source? Who collected it and how?
  • Available to the public? Will I need to request permission to use it? Are there any terms of use? How do I cite the data?
  • In a format I can use for analysis or mapping? Will it require any file conversion or editing before I can use it?
  • Comparable to other data I'm using (if any)? What is the unit of analysis? What is the time scale and geography? Will I need to recode any variables?

 

Analyzing data

The following professional-grade software packages allow you to manipulate and visualize data in very complex ways:

  • SAS - Powerful statistical analysis and data management tool, uses command-line interface, particularly good for ANOVA
  • Stata - Powerful statistical analysis, not as strong at data management as SAS
  • SPSS - Relatively sophisticated data analysis tool, with a user-friendly GUI, geared toward quantitative social sciences data
  • R - Free, versatile option for data analysis and visualization

All of these statistical packages are available through Citrix, in the "Statistics" folder, except for R, which is downloadable from http://www.r-project.org/

 

Where to start

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