what is sse in statistics

In statistics, SSE stands for the sum of squared errors or the residual sum of squares (RSS) . It is a measure of the discrepancy between the data and an estimation model, such as a linear regression. Specifically, SSE is the sum of the squared differences between the predicted values and the actual values of the dependent variable in a regression model. A small SSE indicates a tight fit of the model to the data, while a large SSE indicates a poor fit. SSE is used as an optimality criterion in parameter selection and model selection.