Line-Fit 2.0

The Line-Fit app employs linear regression to analyze the relationship between two variables, commonly referred to as x (independent variable) and y (dependent variable). This approach enables users to establish a linear equation that best fits the observed data.

The standard form of a linear regression equation is represented as Y = a + bX, where Y denotes the dependent variable, X signifies the independent variable, b corresponds to the slope of the regression line, and a represents the intercept (the value of y when x equals zero).

To evaluate the strength of association between the variables, the correlation coefficient is utilized. This coefficient ranges from -1 to 1, providing insight into the degree of correlation observed in the data.

Additionally, the coefficient of determination, denoted as R², quantifies how closely the data points align with the fitted regression line. Generally, higher R² values reflect a more accurate model representation of the dataset, with an R² value of 1.0 indicating a perfect fit.