Regression analysis is a statistical procedure which is associated with finding relationship among two or more variables. It estimates how the values assigned to dependent variables change with the change of one or more independent variables. Regression analysis includes various techniques for observing and analyzing
different variables.

More specifically, it helps a researcher to understand the relationship between dependent and independent variable. Regression is the term used for determining a best fit model for the data in order to describe the relation between variables and thus to predict new information.**How and Why to Use Regression Model**

Regression analysis results in finding a regression model which is best fit to the relationship among various variables in the data. Regression model is very useful in predicting future results also. Regression analysis is most often used in prediction and forecasting. It is also used to relate dependent and independent variables and also to determine the form of relationship.**For example:****(1)** In chemistry, spectroscopic
measurements on different concentrations of a compound are made. Regression model is determined for the relation of concentration to spectrum. After having regression model, a researcher is able to predict unknown
concentrations for new samples.**(2)** During a survey, weights of people of different ages are recorded and a regression model is built.

The researcher can predict various other unknown weights by looking at the model and also the factors by weight varies.

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