What are regression coefficients?

Regression coefficients are numerical values that express the strength and form of the relationship between independent variables and the dependent variable in a regression model. Each coefficient corresponds to a specific independent variable and quantifies how much the dependent variable is expected to change when that independent variable increases by one unit, assuming all other variables remain constant. This makes them essential for interpreting the output of regression analyses, enabling analysts to understand the influence of various predictors on the target outcome.

While it’s true that regression coefficients do indicate the strength of the relationship (as mentioned in the first choice), the more specific definition as provided by the correct answer reflects their role in modeling relationships quantitatively. Additionally, while constants in mathematical equations and factors accounting for variance are related concepts, they do not encapsulate the primary function of regression coefficients as clearly as the relationship with independent variables. Thus, recognizing that regression coefficients signify these relationships helps in properly applying regression analysis in data mining practices.