Hi,
What is the best method to do a failure rate comparison between two process.
If the problem is as simple as you describe (compare two failure rates), then you can use a contingency table analysis. Try these steps:
Here is what my data table looks like, based on your example:
Here is the result of the analysis:
Does this approach help?
Could you provide a bit more information about the kind of data you have or plan to collect? Assuming there is data for a specified time period during which some items fail and some do not, and there are multiple processes you are comparing, your data is censored - items that have not yet failed, might still fail if the experiment/process were to be run for a longer period of time. In that case, some type of survival (e.g., proporational hazards) model might be appropriate. On the other hand, if you have data that spans the lifetime of these items, during which some have failed and some have not, then a classification model could be used. So, if you provide more information about the nature of your data, a better answer can be provided.
To add to Dale's reply, see Help > Books > Reliability and Survival Methods > Life Distribution. There is a feature of this platform to compare groups that is fully explained in this chapter along with examples.
This solution assumes that you have life data, censored or exact.
I agree with Mark's suggestion, but make sure you know exactly what question you want to ask. Mark's continency table will answer the question whether the failure rate differs after 3 months. If you want to answer a more general question - do the failure rates differ - then your data probably is censored, meaning that you have a measurement after 3 months, but the lifetimes are actually longer. I suspect the two analyses will yield similar qualitative comparisons, but not quantitatively equivalent.