Covariates as an additional source of variability in the experiment
Dariusz Mańkowski
d.mankowski@ihar.edu.plPlant Breeding and Acclimatization Institute - National Research Institute (Poland)
https://orcid.org/0000-0002-7499-8016
Janusz Wątroba
StatSoft Polska Sp. z o. o. (Poland)
Abstract
Covariates characterize and complement the variables analyzed in the experiment. They can explain various reactions of observed experimental units to the studied phenomenon or process. The basic statistical tools used to analyze experimental data considering covariates are regression analysis and analysis of covariance. While regression function analysis is a method often used in the analysis of experimental data, this is not the case with analysis of covariance. There are relatively few works presenting the practical use of this method. The aim of this paper is to present the analysis of covariance and its practical use. The paper describes the method of analysis of covariance on the example of a single classification and its use is shown in two agronomical examples.
Keywords:
data analysis, ANCOVA, covariates, mathematical statisticsReferences
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Authors
Dariusz Mańkowskid.mankowski@ihar.edu.pl
Plant Breeding and Acclimatization Institute - National Research Institute Poland
https://orcid.org/0000-0002-7499-8016
Authors
Janusz WątrobaStatSoft Polska Sp. z o. o. Poland
Statistics
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