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Regression analysis is a series of methods applied to determine the relationship between a dependent variable and various independent variables that affect it. As the name suggests, it is used to assess how strong the relationship between them is and what can be their future dependencies.
From its three types, linear regression analysis and multiple regression analysis is most commonly used whereas non-linear regression is used when the independent and dependent variables do not have a linear relationship.
Example: You have data from teenagers telling how their social media addiction affects their studies. Using regression analysis, you can predict the behaviour of a new set of teenagers and predict how their studies are going to be affected.
Conducting exploratory research seems tricky but an effective guide can help.
Regression analysis begins to proceed on the footing of regression model:
Y = α + β1X1 +…+ βkXk + ε
Where, Y is and X1, X2, … Xk are the exploratory variables that affect Y. ε is a residual variable which is the composite effect of the individual differences.
Besides the regression model, the analyst may also take the help of some observed changes in the dependent variable and independent variables in a sample of a population.
As a result, regression analysis yields estimate variables denoted by β1, β2, … βk. These estimates are derived from the values of coefficient that adds up to the average residual 0. The standard deviation of these residuals is very small.
The prediction equation of the summarized result looks like:
Ypred = a + b1X1 + … + bkXk
Regression analysis is used to either predict the behaviour or value of the dependent variable with respect to the changes observed in its corresponding independent variable, OR it is done to just measure the effect of some specific independent variable on the dependent variable.
When it comes to organisations, regression analysis can be a very important practice to leverage against the uncertainty of specific independent variables that keeps on changing over the period, affecting that one dependent variable which is important to the company. The potential field where we can see regression analysis being put to use is the Sales department. Let’s take this as an example, analysts can predict the sales based on how their previous performance was, how much they have invested in advertisements, how efficient their product is and so on.
All these independent variables will be affecting one dependent variable that is sales of the company.
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