Analysis of Covariance

Bayo Lawal ()
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Bayo Lawal: Kwara State University, Department of Statistics and Mathematical Sciences

Chapter 13 in Applied Statistical Methods in Agriculture, Health and Life Sciences, 2014, pp 503-529 from Springer

Abstract: Abstract The analysis of covariance (ANACOVA) is a statistical technique which is a combination of Regression and Analysis of variance. It is used in experiments where besides the observations of primary interests, (variates) one or more other observations are taken on each experimental unit, called CONCOMITANT variables or Covariates. Measurements on the covariates are made for the purpose of adjusting the measurements on the variate. These can be used to increase precision of the experimental comparisons or to throw further light on the treatment effects, or to remove environmental effects. It is assumed that the concomitant variable (X) cannot be controlled by the experimenter but can be observed along with the variable of interest (Y). Thus, analysis of covariance is a method of adjusting for the effects of an uncontrollable nuisance variable. We present examples of the use of covariance analysis.

Keywords: Covariance Analysis; Randomized Complete Block Design; Estimate Regression Coefficient; Partial Regression Coefficient; Irish Potato (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-05555-8_13

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DOI: 10.1007/978-3-319-05555-8_13

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