Regression analysis is a form of predictive modelling technique that investigates the relationship between a dependent and independent variable
Uses of Regression :
- Determining the strength of predictors
- Forecasting an effect
- Trend forecasting
Difference between Linear Regression and Logistic Regression :
- Classification and Regression Capabilities.
- Data Quality
- Computational Complexity
- Classification and Regression Capabilities
- Comprehensible and transparent
Where is it used:
- Evaluating trends and sales estimates
- Analyzing the Impact of Price Changes
- Assessment of risk in financial services and insurance domain
y = mx + c
where y is the dependent variable and x is the dependent variable
So, this method tries to plot a linear graph that is most fit for the model.
It is a statistical measure of how close the data are to the fitted regression line.
Also called Coefficient of determination, or the coefficient of multiple determination
As the value gets close to 1, the better the model becomes.