Abstract
The designs considered in the previous chapters, namely, randomized complete block and Latin square design assume that each block always contain enough experimental units to allow for each treatment (or treatment combination in case of a factorial design) to be contained at least once in each block or in the case of Latin square design in each row or column. In particular, when the number of treatments equals the number of units in a block, the design is very very simple and the analysis becomes straightforward. However, when the number of units in a block is less (in some cases could be more) than the number of treatments, the design is no longer simple and so does the analysis.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Corresponding author
16.1 Electronic supplementary material
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Lawal, B. (2014). Incomplete Block Design. In: Applied Statistical Methods in Agriculture, Health and Life Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-05555-8_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-05555-8_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05554-1
Online ISBN: 978-3-319-05555-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)