Modeling data with a linear model
Linear models are a type of statistical model used to analyze the relationship between a dependent variable and one or more independent variables. In essence, they seek to fit a line that best describes the relationship between these variables, allowing us to make predictions about the dependent variable based on the values of the independent variables. The equation for a simple linear model can be written as follows:
y = β 0 + β 1 x + ε
where y is the dependent variable, x is the independent variable, β 0 and β 1 are coefficients that represent the intercept and slope of the line, respectively, and ε is the error term.
The output of a linear model typically includes the coefficients of the model, which describe the strength and direction of the relationship between the variables, as well as measures of the model’s goodness of fit, such as the R-squared value.
Linear models...
