Describe the variation of the ROAs(Return on Assets) as follows:
The variation of X is calculated as follows:
Linear regression allows us to test hypotheses about the relationship between two variables by quantifying the strength of the relationship between the two variables and to use one variable to make predictions about the other variable.
Estimating the Parameters of a Simple Linear Regression
The Basics of Simple Linear Regression
Linear regression assumes a linear relationship between the dependent and the independent variables. The goal is to fit a line to the observations on Y and X to minimise the squared deviations from the line; this is the least squares criterion—hence, the name least squares regression.
Using notation, the linear relation between the dependent and independent variables is described as follows:
Estimating the Regression Line
Fitting the line requires minimising the sum of the squared residuals, the sum of squares error (SSE), also known as the residual sum of squares:
