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M P?opklpnlbyj?nvnmm M. ?plppkbkv??k? knbnnnnnn??????llp?????tx hikkkhgxxx vj jul?l Sent from my iPhonejukuj?b?mjl jnmnmmm Sorry for keeping things short Gustaf Granath (phd) Plant Ecology Uppsala University

....1221 0.007992 ** ## What is going on here?? I thought the ANOVA table would give me a quite similar result because I only have two levels (of the infl.treat factor) and no interactions in the model. ## I'm afraid I have missed something trivial though so please, be gentle ;) Cheers, Gustaf Granath -- Gustaf Granath (PhD student) Dept of Plant Ecology Evolutionary Biology Centre (EBC) Uppsala University

...gets way to big if I use exp(). To be honest, I get the feeling that Im on the wrong track here. Basically, I want to know how SE is calculated in effect() (all I know is that the reported standard errors are for the fitted values) and if anyone knows what is going on here. Regards, Gustaf Granath

...ch other when I use par(new=TRUE). Is there a way to separate them so y1 and y2 are placed beside each other at each x level, or is this easier to do this with lattice?? I would also like to add error bars but I guess that should not be a problem. For code and data, see below. Cheers, Gustaf Granath, phd student My code so far: #Creating data c(6.34,13.38,17.87)->y1 c(0.85,1.88,2.33)->y2 c(0,1.5,3)->x cbind(y1,y2,x)->mydata data.frame(mydata)->mydata with(mydata, tapply(y1,x,mean))->mean.y1 with(mydata, tapply(y2,x,mean))->mean.y2 #Barplot par(mar=c(5,4,4,4)+0,1) barplot(...

...6659589.591 1585161.876 59.187 6659591.783 1585156.210 59.561 6659592.164 1585156.764 59.266 6659590.352 1585156.154 59.339 6659590.890 1585154.720 59.278 6659592.520 1585155.023 59.250 6659593.127 1585166.690 59.217 Regards, Gustaf _________________________________________________________ Gustaf Granath (PhD student) Dept of Plant Ecology Evolutionary Biology Centre (EBC) Uppsala University Villav?gen 14, SE - 752 36 Uppsala, Sweden Tel: +46 (0)18-471 76 88 Fax: 018 55 34 19 Email: Gustaf.Granath at ebc.uu.se

...ombined as one mean ("the baseline")? or is it something else? Does this number actually tell me anything useful (2.716)?? What does the model (y = intercept + ??) look like then? I can't understand how both factors (A and B) can have the same intercept? Thanks in advance!! Gustaf Granath Dept of Plant Ecology Uppsala University, Sweden