The likelihood principle says that, as the data are the same in both cases, the inferences drawn about the value of "θ" should also be the same. In addition, all the inferential content in the data about the value of "θ" is contained in the two likelihoods, and is the same if they are proportional to one another. This is the case in the above example, reflecting the fact that the difference between observing "X" = 3 and observing "Y" = 12 lies not in the actual data, but merely in the design of the experiment. Specifically, in one case, one has decided in advance to try twelve times; in the other, to keep trying until three successes are observed. The inference about "θ" should be the same, and this is reflected in the fact that the two likelihoods are proportional to each other.