complex linear regression equation example

Based on the price per carat (in hundreds of dollars) of the following 11 diamonds weighing between 1.0 and 1.5 carats, determine the relationship between quality, color and price.Īs described above, we need to solve the following equations: Note too that where j = mĮxample 1: A jeweler prices diamonds on the basis of quality (with values from 0 to 8, with 8 being flawless and 0 containing numerous imperfections) and color (with values from 1 to 10, with 10 being pure white and 1 being yellow). Thus, we can use the Excel function COVAR for the population covariance (or COVARIANCE.P in versions of Excel starting with Excel 2010) or COVARIANCE.S for the sample covariance in versions of Excel starting with Excel 2010 (or the Real Statistics function COVARS), although as we will see below there are ways of calculating all the covariances together.

We can use either the population or sample formulas for covariance (as long as we stick to one or the other). Where the coefficients b m are the solutions to the following k equations in k unknowns.Ĭlick here for a proof of Property 1 (using calculus). Property 1: The regression line has the form Where ŷ i is the y-value on the best-fit line corresponding to x, …, x ik.ĭefinition 1: The best-fit line is called the ( multiple) regression line As in the simple regression case, this means finding the values of the b j coefficients for which the sum of the squares, expressed as follows, is minimum: Given a set of n points ( x 11, …, x 1 k, y 1), …, ( x n 1, …, x nk, y n), our objective is to find a line of the above form which best fits the points. We will now extend the method of least squares to equations with multiple independent variables of the formĪs in Method of Least Squares, we express this line in the form

Complex linear regression equation example