You may try the following to perform anova:
anova(lm(y~x))
or
summary(aov(y~x))
2011/4/13 Ubuntu Diego <ubuntu.di...@gmail.com>
> Hi all,
> I have a very easy questions (I hope). I had measure a property of
> plants, growing in three different substrates (A, B and C). The rest of the
> conditions remained constant. There was very high variation on the results.
> I want to do address, whether there is any difference in the
> response (my measurement) from substrate to substrate?
>
> x<-c('A','A','A','A','A','B','B','B','B','B','C','C','C','C','C') #
> Substrate type
> y <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15) # Results of the measurement
> MD<-data.frame(x,y)
>
> I wrote a linear model for this:
>
> summary(lm(y~x,data=MD))
>
> This is the output:
>
> Call:
> lm(formula = y ~ x, data = MD)
>
> Residuals:
> Min 1Q Median 3Q Max
> -2.000e+00 -1.000e+00 5.551e-17 1.000e+00 2.000e+00
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 3.0000 0.7071 4.243 0.001142 **
> xB 5.0000 1.0000 5.000 0.000309 ***
> xC 10.0000 1.0000 10.000 3.58e-07 ***
> ---
> Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
>
> Residual standard error: 1.581 on 12 degrees of freedom
> Multiple R-squared: 0.8929, Adjusted R-squared: 0.875
> F-statistic: 50 on 2 and 12 DF, p-value: 1.513e-06
>
> I conclude that there is an effect of substrate type (x).
> NOW the questions :
> 1) Do the fact that the all p-values are significant means
> that all the groups are different from each other ?
> 2) Is there a (easy) way to plot, mean plus/minus 2*sd for
> each substrate type ? (with asterisks denoting significant differences ?)
>
>
> THANKS !
>
> version
> platform x86_64-apple-darwin9.8.0
> arch x86_64
> os darwin9.8.0
> system x86_64, darwin9.8.0
> status
> major 2
> minor 11.1
> year 2010
> month 05
> day 31
> svn rev 52157
> language R
> version.string R version 2.11.1 (2010-05-31)
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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