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Bivariate Data Set Definition

Data set in which two measurements (variables) have been made on each experimental unit or respondent.

A bivariate data set is a collection of paired observations or data points involving two variables. Each data point consists of values from two different variables. They are evaluated for patterns, correlations, dependencies and hidden trends not visible when studying the variables individually. Essentially, bivariate data sets are valuable in discovering the interplay and relationships between two variables.

Who relies on a bivariate data set?

Researchers, statisticians, economists, social scientists and data analysts  use bivariate data sets to explore connections between two variables, the results of which can be employed in making decisions, researching and formulating policy.

Why should I care about a bivariate data set?

Bernoulli bivariate data sets involve two categorical variables that represent success or failure in a binary scenario. That’s important because it creates an understanding of the relationship between these two categorical outcomes. That has implications in fields like marketing, healthcare and quality control.