APPLICATION OF MULTIVARIATE ANALYSIS TO AGRONOMIC TRIAL

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dc.contributor.authorDANDAURA, ENOCH NEHEMIAH
dc.date.accessioned2014-02-27T09:12:57Z
dc.date.available2014-02-27T09:12:57Z
dc.date.issued2008-12
dc.descriptionA THESIS SUBMITTED TO THE POST-GRADUATE SCHOOL AHMADU BELLO UNIVERSITY, ZARIA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF MASTER OF SCIENCE DEGREE IN STATISTICS DEPARTMENT OF MATHEMATICS AHMADU BELLO UNIVERSITY ZARIA, NIGERIA DECEMBER, 2008en_US
dc.description.abstractBivariate correlation was carried out on the growth and yield characters of cowpea (Vigna unguiculata [L] Walp) and pod yield and number of pods were observed to be positively and significantly correlated with all the components assessed (Number of Branches, Weight of defoliated leaves, Number of Pods, Length of Pods, Shoot Dry Weight, Plant Height, Number of Leaves, Leaf Area Plant, and Crop Growth Rates) except leaf area index and weight of defoliated leaves. The various parameters exhibited significant interrelationship with one another. Of the 10 growth characters considered in the study, the Principal component analysis shows the reduction of the dimension of the variates to 3 components and these three components explain about 95.57% of the variation. All variables considered shows normality with a linear line indicating that the data observed multivariate normal distribution.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/2833
dc.language.isoenen_US
dc.subjectAPPLICATION,en_US
dc.subjectMULTIVARIATE,en_US
dc.subjectANALYSIS,en_US
dc.subjectAGRONOMIC,en_US
dc.subjectTRIALen_US
dc.titleAPPLICATION OF MULTIVARIATE ANALYSIS TO AGRONOMIC TRIALen_US
dc.typeThesisen_US
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