Reddit mentions of Bioconductor Case Studies (Use R!)

Well, not to sound crass, but you are going to get good at statistics if you are going to interpret microarrays. You might think of microarrays in two parts, getting meaning from the signal, and getting biological meaning from what you that. Both parts require strong statistical knowledge, and with out a good understanding of the process you will really get over your head.

So if someone did the front end analysis (meaning from signal) then you should have a set of deferentially expressed genes, and a bunch of graphs describing the data where they got the DE genes. If your job is to find the biological meaning in the output of this data, then you do not need to know MA / volcano / intensity vs intensity plots, et cetera. You do need to know how to run programs like GSEA (which requires knowledge of the hypergeometric distribution, check Wikipedia, they have a really good explanation of it). There are massive suites of programs to do this, and are pretty study specific on what to do.

If you are looking at the plots you mentioned, you are looking at the front end, asking 'what does my data say?' So you do need to ask yourself, what task are you really trying to get done. If you are looking at MA plots, it is because you are interested in how noisy your data is and if you need to weight each array separately when you go to find DE genes. There are a lot of things that you don't need to fully understand (estimating bayesian priors, how to set up a linear model by hand), but you do need to know what the point each phase of the analysis.
BioConductor Case Studies is a good starting point
Other than that, like SupaFurry said, the bioconductor forums are great, but you will be searching through archived discussions, but that is the main way we get things done, lots of digging.

Hope that helps!