Bivariate Data is data of two quantitative variables. This kind of data is analogous to what is known as univariate data, which is data of one quantitative variable (which could also have been deduced from their prefixes: "bi" means two and "uni" means one).
Bivariate data is used mainly in statistics. It is used in studies that include measures of central tendencies (i.e. mean, median, mode, midrange), variability, and spread. In each study, more than one variable is collected, like in medical studies. Height and weight of individuals might want to be obtained, not just height or weight. Bivariate data is the comparing of two quantitative variables of an individual, and can be shown graphically through histograms, scatterplots, or dotplots.
Based on the data given below, do women generally marry at a younger age than men do?
In this example, we are given two variables: gender and age. The data is given to us below:
10 men's and women's ages of when they were married
25, 26, 27, 29, 30, 31, 33, 36, 38, 40
19, 20, 21, 22, 23, 25, 26, 28, 29, 30
With this data, you can create a histogram to graphically see the results and how they relate to one another. Then, find the mean of each separate chart. The mean age of when men get married is:
25 + 26 + 27 + 29 + 30 + 31 + 33 + 36 + 38 + 40
The mean age of when women get married is:
19 + 20 + 21 + 22 + 23 + 25 + 26 + 28 + 29 + 30
Both distributions are slightly skewed to the right, meaning that more of the data values occur to the left of the mean than to the right.
So, based on our data, women do typically marry at a younger age than men do.