Analysis of Covariance

  • Ronald Christensen
Part of the Springer Texts in Statistics book series (STS)

Abstract

Traditionally, analysis of covariance has been used as a tool in the analysis of designed experiments. Suppose one or more measurements are made on a group of experimental units. In an agricultural experiment, such a measurement might be the amount of nitrogen in each plot of ground prior to the application of any treatments. In animal husbandry, the measurements might be the height and weight of animals before treatments are applied. One way to use such information is to create blocks of experimental units that have similar values of the measurements. Analysis of covariance uses a different approach. In analysis of covariance, an experimental design is chosen that does not depend on these supplemental observations. The concomitant observations come into play as regression variables that are added to the basic experimental design model.

Keywords

Orthogonal Polynomial Design Matrix Regression Variable Potato Yield Balance Incomplete Block Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Ronald Christensen
    • 1
  1. 1.Department of Mathematics and StatisticsUniversity of New MexicoAlbuquerqueUSA

Personalised recommendations