Two-way ANOVA by using Cholesky decomposition and graphical representation

In general, the coefficient estimates of linear models are carried out using ordinary least squares (OLS) method. Since analysis variance is also a model, coefficients can be estimated least-squares this study, in two-way were performed by Cholesky decomposition. The purpose decomposition finding make variables used model being orthogonal such that important easily identified. sum (row, column, interaction) found obtained as result Thus, affect determined more because makes orthogonal. By representing with vectors, how prediction vector ANOVA was created shown. It mentioned affected squares. This method explained detail on sample data and shown geometrically.