Math Portal
Introductory Statistics
Section 1.1 - Classification of Data
Data is a term used to describe information that derives from some form of measurement (counting, using a standard scale, sorting into categories, rank ordering, and so on). You can classify data in several ways according to various qualities. You might classify data as quantitative or qualitative; discrete or continuous; or nominal, ordinal, interval, or ratio level. This chapter describes these different ways of classifying data.
Quantitative and Qualitative data
You can classify data as either quantitative or qualitative. Quantitative data are counts or measurements for which representation on a numerical scale is naturally meaningful. Qualitative data consist of labels, category names, ratings, rankings, and such for which representation on a numerical scale is not naturally meaningful. Distinguishing data as quantitative or qualitative is an important skill in statistics.
Example: A baseball team.
Quantitative Data: number of players, a pitchers earned run average (ERA),number of homeruns, total wins, strike outs
Qualitative Data: color of their uniform, team logo, type of swing for the hitter, handedness (lefty, righty, switch), type of pitches.
Discrete or Continuous data
You can further classify quantitative data as discrete or continuous. Discrete data are quantitative data that are countable using a finite count, such as 0, 1, 2, and so on. Continuous data are quantitative data that can take on any value within a range of values on a numerical scale in such a way that there are no gaps, jumps, or other interruptions. Another way of viewing continuous data is that it is measureable. Recognizing quantitative data as discrete or continuous is another useful skill in statistics.
Example: A baseball team.
Discrete: strike outs, homeruns, hits, walks, plate appearances, saves, doubles, stolen bases
Continuous: batting average, WHIP (walks and hits per inning pitched), earned run average, on-base percentage
Example: A person.
Discrete: number of fingers, number of eyes
Continuous: height, weight, age
Data is a term used to describe information that derives from some form of measurement (counting, using a standard scale, sorting into categories, rank ordering, and so on). You can classify data in several ways according to various qualities. You might classify data as quantitative or qualitative; discrete or continuous; or nominal, ordinal, interval, or ratio level. This chapter describes these different ways of classifying data.
Quantitative and Qualitative data
You can classify data as either quantitative or qualitative. Quantitative data are counts or measurements for which representation on a numerical scale is naturally meaningful. Qualitative data consist of labels, category names, ratings, rankings, and such for which representation on a numerical scale is not naturally meaningful. Distinguishing data as quantitative or qualitative is an important skill in statistics.
Example: A baseball team.
Quantitative Data: number of players, a pitchers earned run average (ERA),number of homeruns, total wins, strike outs
Qualitative Data: color of their uniform, team logo, type of swing for the hitter, handedness (lefty, righty, switch), type of pitches.
Discrete or Continuous data
You can further classify quantitative data as discrete or continuous. Discrete data are quantitative data that are countable using a finite count, such as 0, 1, 2, and so on. Continuous data are quantitative data that can take on any value within a range of values on a numerical scale in such a way that there are no gaps, jumps, or other interruptions. Another way of viewing continuous data is that it is measureable. Recognizing quantitative data as discrete or continuous is another useful skill in statistics.
Example: A baseball team.
Discrete: strike outs, homeruns, hits, walks, plate appearances, saves, doubles, stolen bases
Continuous: batting average, WHIP (walks and hits per inning pitched), earned run average, on-base percentage
Example: A person.
Discrete: number of fingers, number of eyes
Continuous: height, weight, age