The scientist is making a possibly incorrect assumption based on incomplete data. All we know is that the last 20 were successful.
It’s the same as seeing someone flip tails 20 times in a row. Do you think it’s just a coincidence and the chance of heads or tails is still 50/50 or do think there’s something special about the person that makes them flip tails more often?
Or do think there’s something special about the person that makes them flip tails more often?
Yes, that’s the conclusion that the scientist has come to. The chance of getting 20 in a row is so extraordinarily unlikely that it’s reasonable to conclude that the chance is not 50/50 for that particular surgeon.
I think that’s a misunderstanding of statistics and the scientist is making a faulty generalization. You’re only looking at the last 20 and not all of the the surgeries. Imagine the surgeon has had 10020 surgeries and the first 10000 are an even 50/50 split, but the last 20 are all successful. Would you really think you have a higher chance because the last 20 were successful?
And just for fun you can throw 10000 coin flips into libreoffice or excel and see how many in a row can be heads (1) or tails (0). I didn’t get 20 in a row but I did get 19 in a row, and the statistical probability of 50.1/49.9. Something extraordinarily unlikely can still fall within the statistical average.
The scientist is making a possibly incorrect assumption based on incomplete data. All we know is that the last 20 were successful.
It’s the same as seeing someone flip tails 20 times in a row. Do you think it’s just a coincidence and the chance of heads or tails is still 50/50 or do think there’s something special about the person that makes them flip tails more often?
Yes, that’s the conclusion that the scientist has come to. The chance of getting 20 in a row is so extraordinarily unlikely that it’s reasonable to conclude that the chance is not 50/50 for that particular surgeon.
I think that’s a misunderstanding of statistics and the scientist is making a faulty generalization. You’re only looking at the last 20 and not all of the the surgeries. Imagine the surgeon has had 10020 surgeries and the first 10000 are an even 50/50 split, but the last 20 are all successful. Would you really think you have a higher chance because the last 20 were successful?
And just for fun you can throw 10000 coin flips into libreoffice or excel and see how many in a row can be heads (1) or tails (0). I didn’t get 20 in a row but I did get 19 in a row, and the statistical probability of 50.1/49.9. Something extraordinarily unlikely can still fall within the statistical average.