Analysis of Covariance of Models of Sudoku Squares with no Treatment Effects on Concomitant Variable

Abstract

Inclusion of concomitant variable(s) in an analysis of variance (ANOVA) model is an indication that the model is of ANCOVA model provided that there is correlation between the concomitant and response variable. This study employ numerical illustrations of the analysis of covariance of models of Sudoku square with no treatment effects on concomitant variable- Result of the illustration, showed that error variance from the ANCOVA Sudoku square models reduced 12.7761 to 5.5152 for model I; 13.6898 to 6.4690 for model II; 15.7926 to 4.8160 for model III and 16.5152 to 4.9226 for model IV respectively in which the concomitant variable had justified its inclusion in the models. The results showed that adjusted treatment effect is similar across the four ANCOVA models, the correlation coefficient for each of the ANCOVA model is highly positively and the error mean square obtained for ANCOVA models are less than the values of error mean square obtained for ANOVA models of Sudoku square.