1. Regression and Correlation of Data
Objective:
Fit a polynomial with the Least Squares Method

2. Regression and Correlation of Data
Fitting the polynomial with the least squares approach
Least squares method can also be sued to determine
the coefficients:
(n+1 coefficients)
i = 0, 1, 2, …, n
(n+1 equations)

3. Regression and Correlation of Data
In this case, we wish to minimize:
where: M is the number of data points minus 1
The minimization step leads to a system of n+1 normal equations in n+1 unknowns. The unknowns are the coefficients of the polynomial  a0, a1, a2, … , an

5. Regression and Correlation of Data
Gives a system of equations simultaneous equations that can be solved.
Example 45