Citing Data and Statistics
Please remember that whether you use a numeric dataset or a prepared statistical table from an existing source (e.g. Statistical Abstract of the United States) that you do need to cite the source of your information. Depending on the citation style you're required to use for your work it could look like any of the following:
United States Census Bureau. (2000). Census 2000 summary file 3: Maryland raw data. Retrieved 6/5/2010 from http://www2.census.gov/census_2000/datasets/Summary_File_3/Maryland/.
Pew Internet and American Life Project. (2010). Demographics of internet users. Retrieved 6/5/2010 from http://www.pewinternet.org/Trend-Data/Whos-Online.aspx.
Some data sources such as ICPSR provide you with citation information (ICPSR places theirs specifically in the full bibliographic record view).
Data vs. Statistics
What is the difference between Data and Statistics?
In regular conversation, both words are often used interchangeably. In the world of libraries, academia and research there is an important distinction between data and statistics. Data is the raw information from which statistics are created. Put in the reverse, statistics provide an interpretation and summary of data.
- Statistical tables, charts, and graphs
- Reported numbers and percentages in an article
If you’re looking for a quick number, you want a statistic. A statistic will answer “how much” or “how many”. A statistic repeats a pre-defined observation about reality.
Statistics are the results of data analysis. It usually comes in the form of a table or chart. This is what a statistical table looks like:
- Machine-readable data files, data files for statistical software programs
If you want to understand a phenomenon, you want data. Data can be analyzed and interpreted using statistical procedures to answer “why” or “how.” Data is used to create new information and knowledge.
Raw data is the direct result of research that was conducted as part of a study or survey. It is a primary source. It usually comes in the form of a digital data set that can be analyzed using software such as Excel, SPSS, SAS, and so on. This is what a data set looks like:
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