Introduction
It’s a statistical technique utilized in information evaluation to discover the connection between a dependent variable and two or extra unbiased variables. It extends the easy linear regression mannequin, which entails predicting a dependent variable primarily based on a single unbiased variable, to deal with conditions the place a number of elements might affect the end result.
Within the a number of regression mannequin, the connection between the dependent variable.
The a number of regression mannequin goals to estimate the values of the coefficients 
that minimizes the sum of squared variations between the noticed values of Y and the values predicted by the mannequin. This course of is usually finished utilizing statistical strategies corresponding to the strategy of least squares.
Key ideas in a number of regression embrace:
a) R-squared(R^2): A measure of how properly the unbiased variables clarify the variability within the dependent variable. It ranges from 0 to 1, with greater values indicating a greater match.
b) Coefficients and P-values: Coefficients symbolize the power and route of the connection between every unbiased variable and the dependent variable. P-values assist assess the statistical significance of those relationships.
c) Multicollinearity: The presence of excessive correlations amongst unbiased variables, which may complicate the interpretation of particular person coefficients.
d) Adjusted R-squared(R^2): A modified model of R-squared that adjusts for the variety of unbiased variables, offering a extra dependable measure of the mannequin’s goodness of match.
Conclusion
A number of Regression is a sort of linear regression that’s used primarily when we’ve multiple unbiased variable that’s used to foretell the dependent variables. It’s utilized in economics,social sciences, and pure sciences.
