Linear correlation: variables are said to have a linear correlation when the changes in one variable are proportional to changes in the other variable.

Linear regression: It is the technique for finding the equation with the form y=ax+b that best figures the relationship between the x (independent) and y variables (dependant).

Line of best fit: Is a straight line that passes the data points on a scatter plot. This line is drawn closest to all the points on the scatter plot and best signifies the relationship between two variables.

The correlation coefficient: This tells whether or not there is a linear relationship between the x and y values.

Dependent variable: is also known as the response variable.

Independent variable: is also known as the explanatory variable.

Scatter plot: a graph drawn to show the relationship between the dependent and the independent variable.

Method of performing Linear Regression:

Classifying Linear Correlation: