Bivariate data analysis involves the analysis of two 'variables' simultaneously. It is important in the statistics used widely in everyday situations and in fields including education, business, economics, government, etc. While most single-variable data analysis methods are used for descriptive purposes, bivariate data analysis explores relationships between variables, including through the use of scatter plots and lines of best fit, and is generally used for explanatory purposes. A researcher investigating the proportion of eligible voters who actually vote in an election might consider a single variable, such as age. If wanting to use a bivariate approach, the researcher might compare age and gender, or age and income, or age and education, etc.
Obtained from https://educationstandards.nsw.edu.au/wps/portal/nesa/k-10/learning-areas/mathematics/mathematics-k-10/content/743
A student: