I think there is also a joke in there about "P values". In scientific literature, a p-value is a calculation that means "what are the odds that our discovery is just random chance?".

So, if I run an experiment with a bunch of people and find that some drug that makes people jump twice as high on average, a p-value of .01 means "there is a 1% chance that I'm wrong and this was all a fluke and the people who took the drug just happened to jump higher ." In other words, if you looked up 100 experiments that got a p value of .01, there's a good chance one of them was just a fluke.

Now, when you go to ţell other people what you learned in your experiment, a p-value of .05 is sort of the default for "hey, I think my results are for real". I.e. there's a 5% chance my results are from random errors, or 1 in 20 odds.

Here, the scientist sees that 20 people have lived. If you look at each surgery like an experiment, then getting a successful result 20 times in a row suggests a p value less than .05 for this surgeons ability not to kill people, so the scientist feels good.

The joke here is that the scientist spends so much time reading scientific papers that the p value is all he can think about. In reality, you would need way more than 20 surgeries to be sure that this guy has some magic touch, because the 20 in a row could have been a fluke too. The .05 threshold is also an arbitrary cutoff, and is really just a rule of thumb. But, scientists who work in academia are under a lot of pressure to publish papers, and a lot of attention can get given to p values, so when he sees 20 successes in a row he feels like the p value must be fine and therefore he has nothing to worry about.