Linear Regression and Non-Linear Regression

Linear regression and non-linear regression are two types of statistical models used to analyze the relationship between a dependent variable and one or more independent variables. The main difference between these models is the type of mathematical function used to describe the relationship between the variables.

Linear regression is a statistical model that assumes a linear relationship between the dependent variable and one or more independent variables. This means that the relationship between the variables can be described by a straight line. Linear regression models are widely used in many fields, including economics, social sciences, and ______ _________ _____ ________ __________ ______ __________ _________.
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