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I?m entirely stumped on this particular issue and really hoping someone has some advice for me. I am running a covariant model in lm I would like to give the standard errors or the confidence intervals for the fitted lines. I?ve been using the dataset OrangeSprays where I want lines for each level of treatment over the covariant ?colpos?. I?ve been able to calculate intercepts and slopes for

I created this graph in ggplot and added ablines to the different facets by specifying with subset commands. As you might see, there are still a few issues. 1.) I would like to have the diamonds in a grey scale instead of colors. I accomplished this (see graph 2) until I overwrote the label title for the treatments and the colors came back (graph 1). I used these two commands: p=ggplot(data =

This is what I have now so far. p=ggplot(data = test, aes(x = YEAR, y = TOTAL, colour = TREATMENT)) + geom_point() + geom_smooth(method = "lm", se=FALSE) + facet_wrap(~COUNTRY) > p +scale_x_continuous(limits=c(1,4)) http://r.789695.n4.nabble.com/file/n3626510/graph.gif I would also like to: 1.) change the headline for the faced wraps ?high? and ?low?. Is there any other way of

Hi there, I am having a little problem with combining three scale_manual commands in a facet plot. I am not able to combine the three different characteristics, instead ending up with three different descriptions next to the graph for the same geom. I would like to see two separate labels (not three); one describing lines 1-7 and the other 8-14. For each of the treatments (A-B) I want a

I am new and self taught in R, so please bear with me. I want to create two scatter plots side by side. The data set includes measurements from two different countries with 7 treatments over a timeline (x-axis). Problem 1 I want to have each plot to include the data from one of the countries with 7 regression lines of the treatments, but I do no know how to divide the data between them. This is