What are the various methods of linear regression analysis?
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What is Regression Analysis?
Regression analysis is a form of predictive modelling technique which investigates the relationship between adependent (target) and independent variable (s) (predictor). This technique is used for forecasting, time series modelling and finding the causal effect relationshipbetween the variables. For example, relationship between rash driving and number of road accidents by a driver is best studied through regression.
Regression analysis is an important tool for modelling and analyzing data. Here, we fit a curve / line to the data points, in such a manner that the differences between the distances of data points from the curve or line is minimized. I’ll explain this in more details in coming sections.
techniques do we have?
There are various kinds of regression techniques available to make predictions. These techniques are mostly driven by three metrics (number of independent variables, type of dependent variables and shape of regression line). We’ll discuss them in detail in the following sections.
For the creative ones, you can even cook up new regressions, if you feel the need to use a combination of the parameters above, which people haven’t used before. But before you start that, let us understand the most commonly used regressions:
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Regression analysis is a form of predictive modelling technique which investigates the relationship between adependent (target) and independent variable (s) (predictor). This technique is used for forecasting, time series modelling and finding the causal effect relationshipbetween the variables. For example, relationship between rash driving and number of road accidents by a driver is best studied through regression.
Regression analysis is an important tool for modelling and analyzing data. Here, we fit a curve / line to the data points, in such a manner that the differences between the distances of data points from the curve or line is minimized. I’ll explain this in more details in coming sections.
techniques do we have?
There are various kinds of regression techniques available to make predictions. These techniques are mostly driven by three metrics (number of independent variables, type of dependent variables and shape of regression line). We’ll discuss them in detail in the following sections.
For the creative ones, you can even cook up new regressions, if you feel the need to use a combination of the parameters above, which people haven’t used before. But before you start that, let us understand the most commonly used regressions:
Plzzzzz mark me brainlist plzz... As soon as possible
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