Calculating the equations of the lines of best fit

In this section, we’ll dive into the process of calculating the equation of the line of best fit for both simple and multiple linear regression. While equations may seem daunting, we’ll break them down step by step to ensure a clear understanding. By mastering the equations behind the lines of best fit, you’ll gain a deeper appreciation for the underlying mechanics of linear regression.

For simple linear regression, the equation of the line of best fit can be represented as follows:

y = a + bx

Here, y is the dependent variable, x is the independent variable, a is the y-intercept (the point where the line intersects the Y-axis), and b is the slope (which determines the steepness of the line):

Figure 5.4: Line of best fit and the equation of the line

To calculate a and b, we can use the following formulas:

b = ∑ i=1 n  (x i − x̄...