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Tag Info

This tag is for questions on (linear or nonlinear) regression, which is a way of describing how one variable, the outcome, is numerically related to predictor variables. The dependent variable is also referred to as $~Y~$, dependent or response and is plotted on the vertical axis (ordinate) of a graph.

Regression is a statistical measurement used in finance, investing and other disciplines that attempts to determine the strength of the relationship between one dependent variable (usually denoted by $$~Y~$$) and a series of other changing variables (known as independent variables).

Types of Regression –

• Linear regression
• Logistic regression
• Polynomial regression
• Stepwise regression
• Stepwise regression
• Ridge regression
• Lasso regression
• ElasticNet regression

The two basic types of regression are linear regression and multiple linear regression.

The general form of each type of regression is:

• Linear regression: $$~Y = a + b~X + u~$$
• Multiple regression: $$~Y = a + b_1~X_1 + b_2~X_2 + b_3~X_3 + ... + b_t~X_t + u~$$

Where:

• $$Y =~$$ the variable that you are trying to predict (dependent variable).
• $$X =~$$ the variable that you are using to predict Y (independent variable).
• $$a =~$$ the intercept.
• $$b =~$$ the slope.
• $$u =~$$ the regression residual.

There are multiple benefits of using regression analysis. They are as follows:

$$1.~$$ It indicates the significant relationships between dependent variable and independent variable.

$$2.~$$ It indicates the strength of impact of multiple independent variables on a dependent variable.

Reference:

https://en.wikipedia.org/wiki/Regression_analysis

This tag often goes along with the tag.