An application of analysis of covariance technique in studying the effect of concomitant variables on sales of grand cereals oil

Abstract

Analysis of covariance (ANCOVA) is an extension of analysis of variance (ANOVA) that allows modelling and adjustment for input variables that are measured but not randomized or controlled in the experiment. ANCOVA tests whether factors have an effect after removing the variance due to covariates. Data for this work are on sales of grand cereals oil being produced by Grand Cereals and Oil Mills Limited Company located in Jos, Plateau State, Nigeria. Effects of sales managers’ age and gender on the recorded sales of this product were first examined using the ANOVA technique. Then the ANCOVA technique was employed to investigate whether sales differ by the sales managers’ age and gender and whether there is significant interaction effect between these variables (age and gender) in terms of the average sales after adjusting/controlling for the sales volume. The ANOVA result shows that gender and age have a statistically significant effect on sales (p< 0.001) and that the fitted model accounted for 49.8% of variation in the data, with a mean squared error (MSE) of 70.782. The effect of age after adjusting for the covariate was observed to be significant (p< 0.001). The fitted ANCOVA model accounted for about 80.5% of the total variation in the sales data with a MSE of 27.028, which is a substantial reduction, indicating a sharp increase in the power of the test to detect the significant effects. We then conclude that, the middle age group has a significant effect on the volume of sales than the young and old considering their work experience and their strength.