model parameter

In statistics, a parameter is a variable whose value is sought through sample evidence. This value, known as an estimate or statistic, helps characterize a larger population.12

Regression analysis uses parameters to model relationships between variables. In simple linear regression, the model is (y = \beta_0 + \beta_1 x + \epsilon), where (\beta_0) and (\beta_1) are model parameters, and (\epsilon) is an error term. The estimated regression equation, (\hat{y} = b_0 + b_1 x), uses calculated estimates ((b_0) and (b_1)) to approximate this relationship. This equation can then predict the dependent variable ((y)) based on the independent variable ((x)).34