Quantitative variable

Quantitative variable

·         Quantitative or numerical data arise when the observations are frequencies or measurements.

·         The data are said to be discrete if the measurements are integers (e.g. number of  employees of a company, number of incorrect answers on a test, number of participants in a program…)

·         The data are said to be continuous if the measurements can take on any value, usually within some range (e.g. weight).   Age and income are continuous quantitative variables. For continuous variables, arithmetic operations such as differences and averages make sense.

Analysis can take almost any form:

Þ      Create groups or categories and generate frequency tables.

Þ      All descriptive statistics can be applied.

Þ      Effective graphs include: Histograms, Stem-and-Leaf plots, Dot Plots, Box plots, and XY Scatter Plots (2 variables).

·         Some quantitative variables can be treated only as ranks; they have a natural order, but  these values are not strictly measured.  Examples are:  1) age group (taking the values child, teen, adult, senior), and 2) Likert Scale data (responses such as strongly agree, agree, neutral, disagree, strongly disagree).  For these variables, the distinction between adjacent points on the scale is not necessarily the same, and the ratio of values is not meaningful.

Analyze using:

Þ      Frequency tables

Þ      Mode, Median, Quartiles