Optimizing Prediction Systems With Linear Regression

Abstract

Linear regression is a fundamental statistical technique used to model the relationship between a dependent variable and one or more independent variables. By establishing a linear equation that best fits the observed data, it enables the prediction of the dependent variable based on known values of the independent variables. This method not only quantifies relationships but also provides critical insights for trend analysis and forecasting, making it an indispensable tool across various domains. As one of the most widely applied statistical techniques, linear regression plays a pivotal role in predictive modeling, data analysis, and informed decision-making. This paper explores the core principles of linear regression, examining its applications, significance in predictive systems, and its extensive use in fields such as finance, healthcare, and artificial intelligence..