R-squared
R-squared, also known as the coefficient of determination, is a statistical measure that represents the proportion of the variance in the dependent variable that is predictable from the independent variable(s) in a regression model. It ranges from 0 to 1, where 0 indicates that the model explains none of the variability, and 1 indicates that it explains all the variability. It is commonly used in linear regression to assess the goodness of fit of a model.
Developers should learn R-squared when working with data analysis, machine learning, or statistical modeling to evaluate how well their regression models fit the data. It is particularly useful in scenarios like predictive analytics, A/B testing, or financial forecasting to quantify model performance and compare different models. Understanding R-squared helps in making informed decisions about model selection and identifying potential overfitting or underfitting issues.