I'm using JMP to analyze some sample data to make predictions about the population. My sample is from a destructive QC test, so I obviously want to minimize my sample. I have a response (my Y) and a known factor (a very strong and consistent correlation that is measurable by non-destructive means) but the exact relationship between them varies from lot to lot (the slope and y offset vary).
So, in JMP, I am fitting a line and then showing the "confidence limits for an individual predicted value" which I believe gives me an indicator of how the population is likely to behave. So I'm using that plot to make disposition decisions. I want to automate this process, perhaps using R, but I'm a total novice at R. I could do the math if I was just dealing with a mean and standard deviation, but I don't know how to do it with a fit line and a known factor. Can someone please give me either the general information on how to get the confidence limits around the line, or else tell me how to do the whole thing in R?