Research Topics:

Data Analysis | Regression Analysis

Content Type:

Glossary

Bivariate Regression Analysis Definition

Analysis of the strength of the linear relationship between two variables, the independent variable and the dependent variable.

Bivariate regression analysis explores the relationship between two variables. This statistical method determines whether there is a linear relationship between the variables. Fitting a regression line into the data illustrates how changes in one variable are associated with changes in another. This analysis provides insights into the scope of the relationship. An example of how these analyses work is exploring the variables associated with birth rate. By conducting a bivariate regression, a statistically significant relationship between birth rate and other variables like income, education and health care exists.

Who relies on bivariate regression analysis?

Researchers, economists, social scientists and analysts across various fields use bivariate regression analysis to make predictions, understand patterns and test hypotheses.

Why should I care about bivariate regression analysis?

Bivariate regression analysis uncovers connections between two variables, thus assisting business and marketing professionals to make informed decisions. This analysis provides quantitative insights for such tasks as predicting sales based on marketing expenses or examining the impact of interventions.