Information that can be expressed in numerical terms, counted, or compared on a scale.

Data that can be conveyed as a specific, measurable number or value.

data dealing with numeric values that are either calculated or are calculable. Measurements and computations are typical examples: "Net-Pay," "Quantity Ordered," "Elapsed Time," "Percent of Gross," etc. It is sometimes difficult to differentiate Quantitative data from Indicative data. Indicative data will often use numeric values for identification purposes, such as "Invoice Number," "Purchase Order Number," "Customer Number," etc. However, it would be a mistake to use these numbers for quantitative purposes (aside from counting the number of occurrences). (See Descriptive Data and Indicative Data).

information which can be analyzed usefully by being counted and compared. See Qualitative data.

observable, countable occurrences/non-occurrences of behaviors (what occurs).

Information that is represented numerically so you can assign ranks or scores, or determine averages and frequencies. Also Called HARD DATA.

capture information that is numeric including variables like personal income, amount of time, or a rating of an opinion on a scale from 1 – 5. Quantitative data are used with close-ended questions where users are given a limited set of possible answers. They are best for responses that fall into a relatively narrow range of possible answers.

data with values are numerical; can be discrete (counted) or continuous (measured).

Numerical information that can be summarized in statistics for analysis purposes.

Data based on "hard numbers" such as enrollment figures, dropout rates and test scores (as opposed to qualitative data).

Numerical information gathered in a structured way.

Data that lends itself to numerical representation and arithmetic manipulation.

Data which can be represented numerically

Statistical information in the form of numbers normally derived from a population in general or samples of that population. This information is often analysed using descriptive statistics, which consider general profile distributions and trends in the data, or using inferential statistics, which are used to determine significance within relationships of differences in the data. Top of this page