Regression analysis is the method used to extract and summarize the variation in a set of response variables that can be explained by a set of explanatory variables. It helps identify and quantify the relationships between variables, allowing for predictive modeling and inference.
You can then use any form or method in Regression Analysis, to solve your proposed problem....
The method you are referring to is called linear regression. Linear regression is a linear approach for modeling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used.
The method used to extract and summarize the variation in a set of response variables that can be explained by a set of explanatory variables is called regression analysis.
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