Once we know our data is normal and we have our aov()
object, we can use one of two commands on this object to generate our statistical result. The normal way to do so is to use the anova()
command.
anova(weeds.aov) # run an anova on the object
## Analysis of Variance Table
##
## Response: flowers
## Df Sum Sq Mean Sq F value Pr(>F)
## species 2 2368.6 1184.31 9.0966 0.0004811 ***
## Residuals 45 5858.7 130.19
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# WOO! Significance!
Alternatively we can use the summary()
command on our aov()
object to generate the same result. For most other analyses, such as linear regressions and mixed models, we will use the summary()
command exclusively.
Because we created an aov()
object, the summary()
command automatically does an ANOVA.
summary(weeds.aov) # print a summary of the object. In this case the summary is an anova
## Df Sum Sq Mean Sq F value Pr(>F)
## species 2 2369 1184.3 9.097 0.000481 ***
## Residuals 45 5859 130.2
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Using the summary() command, what is the F-value for fragment in the Insecticide ANOVA?
14.94