Data vs. Statistics
The terms data and statistics are often used interchangably, but in research the two are different. It's important to understand the distinction to determine what you need.
Data are raw ingredients from which statistics are created, and data often need software (e.g. SPSS, Stata, etc.) to be manipulated. Statistcal analysis can be performed on data to prove a hyopthesis, show relationships among the variables collecte, generate custom tables, do Regression, t-test, ANOVA. Through secondary data analysis, many different researchers can re-use the same data set for different purposes.
Statistics are in a "ready to use" format where the data have already been analyzed and processed to produce information in an easy to read format such as facts, figures, charts, tables, and graphs. Statistics are useful when you just need a few numbers to support an argument (ex. In 2003, 98.2% of American households had a television set--from Statistical Abstract of the United States).
On the most basic level it will help to think of data as the entire collection of information gathered during the process of a survey. A statistic takes that data and refines it down to a single number or percentage in order to answer a specific question - such as "what is the median age of Vanderbilt freshmen".
As a general rule of thumb:
If what you need is a number to back up your argument, then a statistic will probably do.
If, on the other hand, you need to manipulate the information to answer a new or different question, you will likely need to get your hands on some data.
Some data types:
Numeric Data are made up of numbers. Numeric Data are processed using statistical software like SPSS, Stata, or SAS.
Qualitative Data are data that describe a property or attribute. Examples of qualitative data are interviews, case studies, comments collected on a questionnaire, etc.
Spatial Data are geographic information that is used for analysis with GIS software like ArcGIS.
Primary Data are data collected through your own research study directly through instruments such as surveys, observations, etc.
Secondary Data are data from a research study conducted by someone else. Usually when you are asked to locate statistics on a topic you are using secondary data. An example of secondary data are statistics from the Census of Population and Housing.
It can be challenging to find and interpret health statistics. If you're having trouble finding or using statistics, these guides are a good place to start: