Analysis of Covariance in Completely Randomized Design

Abstract

General experimental analysis external factors that may affect the values observed in the experimental unit are controlled. But in some experiments Subject is unable to control external factors that may interfere with the experimental unit. If the experimenter takes the values obtained from the observations in the experimental unit to analyze the variance. In orders to determine the influence of different treatments, the results obtained from the analysis are not reliable. Therefore, if an experiment wants to study the influences caused by the factors of interest in the analysis, these disregard factors must be excluded. In orders to know the effect of the factors that are genuinely interested in this method of analysis is called covariance analysis, or analysis of covariance (Analysis of Covariance (ANCOVA). In the experiment, these disregard factors were referred to as Covariate or Covariate (Covariate Variable), that covariance analysis Independent variables or factor levels are group variables. The covariates and dependent variables were quantitative variables. The experimental layout was arranged according to the experiment plan of interest, such as the Completely Randomized Design: CRD, Randomized Complete Block Design: model or other types, but here, it describes only the CRD experimental layout.