




Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
An example of how to perform a covariance analysis of peanut fertilizer data using sas. The data is input using the data step, and the proc glm procedure is used to fit a linear model and estimate the covariance matrix. The results are then displayed using proc print and proc gplot.
Typology: Study notes
1 / 8
This page cannot be seen from the preview
Don't miss anything!





Covariance^ Analysis
of^ Peanut^ Fertilizer
Data^
Obs^ fertilizer
yield^ height 1 C 12.2^452 C 12.4^523 C 11.9^424 C 11.3^355 C 11.8^406 C 12.1^487 C 13.1^608 C 12.7^619 C 12.4^50 10 C^
Covariance^ Analysis
of^ Peanut^ Fertilizer
Data^
The^ GLM^ ProcedureClass^ Level^ InformationClass Levels^
Values fertilizer^
Number^ of^ Observations
Read^30 Number^ of^ Observations
Used^30 Covariance^ Analysis
of^ Peanut^ Fertilizer
Data^
The^ GLM^ Procedure Dependent^ Variable:
yield^ Yield
Sum^ of Source^
DF^ Squares
Mean^ Square
F^ Value^ Pr
Model^
Error^
Corrected^ Total^
29 214.7936667R-Square Coeff^ Var^
Root^ MSE^ yield
Mean 0.998055^ 1.
Source^
DF^ Type^ I^
SS^ Mean^ Square
F^ Value^ Pr
fertilizer^
height^
Source^
DF^ Type^ III^
SS^ Mean^ Square
F^ Value^ Pr
fertilizer^
height^
Covariance^ Analysis
of^ Peanut^ Fertilizer
Data^
The^ GLM^ Procedure Dependent^ Variable:
yield^ YieldContrast
DF^ Contrast^
SS^ Mean^ Square
F^ Value^ Pr
Modified^ vs.^ Standard
Slow-release^ vs.
Fast-release^