LINEAR REGRESSION
Important Concepts Before Starting Linear Regression
Independent Variable (Predictor)
The independent variable is the factor that you manipulate or control in an experiment or analysis to
observe whether it causes any change. It is also called the predictor or explanatory variable because it is
the input that potentially influences the outcome.
Dependent Variable (Response)
The dependent variable is what you measure or observe to see if it responds to the changes in the
independent variable. It is also known as the response or outcome variable because it depends on the
input from the independent variable.
Example: Working Hours and Wages
Consider a simple scenario where the amount of wages earned depends on the number of hours worked.
For each hour worked, a person earns 10 dollars. This relationship can be expressed as:
Wages=10×Hours WorkedWages=10×Hours Worked
Here, the wages are the dependent variable because they depend on the working hours, which is the
independent variable. As the working hours increase, the wages increase proportionally, illustrating a clear
dependency.
Definition of Linear Regression
Linear regression is a statistical technique used to model the relationship between a dependent variable
and one or more independent variables by fitting a linear equation to observed data.
Important Concepts Before Starting Linear Regression
Independent Variable (Predictor)
The independent variable is the factor that you manipulate or control in an experiment or analysis to
observe whether it causes any change. It is also called the predictor or explanatory variable because it is
the input that potentially influences the outcome.
Dependent Variable (Response)
The dependent variable is what you measure or observe to see if it responds to the changes in the
independent variable. It is also known as the response or outcome variable because it depends on the
input from the independent variable.
Example: Working Hours and Wages
Consider a simple scenario where the amount of wages earned depends on the number of hours worked.
For each hour worked, a person earns 10 dollars. This relationship can be expressed as:
Wages=10×Hours WorkedWages=10×Hours Worked
Here, the wages are the dependent variable because they depend on the working hours, which is the
independent variable. As the working hours increase, the wages increase proportionally, illustrating a clear
dependency.
Definition of Linear Regression
Linear regression is a statistical technique used to model the relationship between a dependent variable
and one or more independent variables by fitting a linear equation to observed data.
