Intuitively, the existence of categories at 2% and 3% make the conclusion clear. If the 1995 data isn't made up, then it is very rare that a project falls into one of these categories at all - respectively 1/50 and 1/30 chances. So the chance that our small sample of 9 projects happens to contain one each of these kinds of projects is very small to start with, about 9/150.
Given that we know nothing about how the projects themselves were distributed between the categories, we can't actually say this with any confidence. It's possible, for example, that the 2% category actually receives many projects on average, but they're all cheap.
If you assume that the project costs are normally distributed, then that assumption makes the 1979 data inherently unlikely, no matter how close the percentages are to 1995: the existence of a category receiving 2% of the funding means that at best you have a data point which is only 18% of the mean (and another point at 27%). That just doesn't happen for normal distributions (unless the variance is so large that the model becomes ridiculous anyway, due to the huge probability of it giving you negative numbers).
It's actually quite plausible that cheaper projects have a greater chance of falling into the rare category of successful projects, as the original 1979 defined success - "used without extensive rework". It's also quite possible that project size isn't normally distributed.
What I seem to have trouble conveying is my intuition that the fit is too close to be true - that in general if you have a multinomial distribution with five categories, and you draw a small sample from that distribution, it is quite unlikely that your sample frequencies will c...
What I'm trying to figure out is, how to I determine whether a source I'm looking at is telling the truth? For an example, let's take this page from Metamed: http://www.metamed.com/vital-facts-and-statistics
At first glance, I see some obvious things I ought to consider. It often gives numbers for how many die in hospitals/year, but for my purposes I ought to interpret it in light of how many hospitals are in the US, as well as how many patients are in each hospital. I also notice that as they are trying to promote their site, they probably selected the data that would best serve that purpose.
So where do I go from here? Evaluating each source they reference seems like a waste of time. I do not think it would be wrong to trust that they are not actively lying to me. But how do I move from here to an accurate picture of general doctor competence?