Chapter 4 - Using Data in DataFerrett

The majority of the data that is included in TheDataWeb for DataFerrett are Microdata sources. This data structure is collections of individual responses to questions asked once in a particular survey or census, or in a series of survey questions asked over time. The survey questionnaires may be completed directly by respondents or the responses may be derived from interviews during which questions are read and responses recorded by an interviewer. The information can also be answers to questions on an administrative form. To use microdata sources, you need to choose what responses, or variables, are available (for example, age and income). You will also want to define which population of respondents you will want to study (for example, employed women) according to what the possible answers were to the questions and how they are recorded (values). Values are the possible responses for each question or section of a form.

For example, the form may have asked about motor vehicle ownership, with the responses being 1=Car, 2=Van, 3=Truck, 4=Other. You will need to know how the answers (values) are coded and think about how you might want to add categories together or compare categories of answers. Values may be ranges of numbers, amounts (e.g., dollars or ounces), or codes that represent certain categories (e.g., age ranges or number of years attended school).

Values may be categorical, integer, or alpha/character. Responses can be summarized for specific topics to create specific views of the data. Do-it-yourself tabulations can be produced for any desired set of variables to study the characteristics of specially defined populations.

This part of DataFerrett is what allows you to select specific items from surveys, specific values for those items, and then download the data or create your own custom tables and graphs.

The majority of the data in DataFerrett is microdata.

Aggregate Data

There are a few sources of Aggregate data in DataFerrett. Specifically, Aggregate data is data which has already been summarized or added up, usually for specific geographical units or some other unit, such as industry classifications. In this case, each record is a geographical unit and there is no summing needed to get the totals for the geographies. The geographic variable is usually dropped into a column and the "complimentary" variables are then dropped individually into it's own column. There can be no "nesting" of aggregate data variables. One major source of aggregated data is the Decennial Census of Population and Housing, which is the 2000 Census Long Form Summary File 3.

Time Series Data

Time Series Data is a sequence of observations which are ordered in time (or space). If observations are made on some phenomenon throughout time, it is most sensible to display the data in the order in which they arose, particularly since successive observations will probably be dependent. Time is called the independent variable.

Longitudinal Data

Longitudinal Data is a panel data in which many units are observed over multiple time periods. The Bureau of Labor Statistics' National Longitudinal Surveys (NLS) program collects data from a particular age group of people over many years on an annual or biennial basis. The panel data track the same sample of individuals over many time periods.