What is meant by regression coefficients?

Regression coefficients represent the parameters in a regression equation used to predict the value of the dependent variable based on one or more independent variables. Specifically, these coefficients include both the slope and the intercept of the regression line.

In a simple linear regression model, the equation is often expressed as ( Y = a + bX ), where ( Y ) is the dependent variable, ( X ) is the independent variable, ( a ) is the intercept, and ( b ) is the slope. The intercept indicates the expected value of ( Y ) when ( X ) is zero, while the slope represents the change in ( Y ) for a one-unit change in ( X ). Therefore, the term 'regression coefficients' encompasses both these values collectively, which is why the choice accurately captures the concept.

Understanding regression coefficients is essential for interpreting the relationship between variables and assessing the strength and direction of their association. This is particularly crucial in data-driven decision-making, where insights gathered from data analysis can guide strategic choices and predictions.