Regression is estimation(correlation) – of the independent variable with the dependent variable.(We can make a scatter plot whenever you have data that relates two values together).
We need an equation – which models the data for y(dependent) for any x(independent), that is, the correlation between them.
If the data points moves up – there is a positive slope/correlation – and vice versa down a negative slope/correlation. If the data points are all over the place there is no correlation.
Given n(number of data points), the formula for the basic regression line is y^ = mx + b
To find m(the slope), which represents the predictive direction and change rate, we use the following formula:
m = (n∑xy-∑x∑y)/(n∑x²-(∑x)²)
To find b(the y intercept), which represents the bias when there is no information regarding x, we use the following:
b = (∑y-m∑x)/n
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