NikkiL
\(\frac{1}{3}\) of golfers also play tennis, \(\frac{3}{5}\) of tennis players also surf. \(\frac{4}{7}\) of surfers also ski. If a golfer is selected at random, is the chance that that golfer also skis greater than \(\frac{1}{2}\) ?
(1) All golfers who do not play tennis also surf.
(2) All tennis players also play golf.
ShreyasJavahar
Hello
IanStewart, could you please help with this?
Sure - say we use both Statements, and there are 15 golfers. We know 5 golfers play tennis, and there are 5 tennis players in total, from Statement 2. From the "3/5" in the question stem, we know 3 of these golfer-tennis-players is also a surfer. We also know the remaining 10 golfers are also surfers, from Statement 1. So we have 13 tennis players who are surfers in total.
But that's really all we know, because there's no connection between the last fraction in the stem, the "4/7", and anything else we just learned. Maybe there are 7,000,000 surfers in total, most of whom don't golf at all, and 4,000,000 of them ski, so 3,000,000 of them don't ski. Our 13 tennis players who are surfers could all belong to that group of 3,000,000 non-skiers, or they could all belong to that group of 4,000,000 skiers. And we don't know anything about the other two golfers (the two who only play tennis) either. So the probability the question asks for could be anything between 0 and 1, and the answer is E.
It's a bit of a confusing question at first, and I imagine many people will just start multiplying the fractions as if it were a standard probability question -- that was the mistake in the solution posted above by physiltant (who realized their mistake but never corrected it). physiltant was assuming all of the people were golfers, and then was further assuming that when, say, "4/7 of surfers also ski", that you could then say that "from the group of tennis players who surf, 4/7 of them must ski", and we have no reason to think that's true. It's maybe a bit confusing to see in the context of this question, but the principle is the same in this example: if you knew in country X that 10% of people were unemployed, there'd be no reason to expect that exactly 10% of people with Engineering degrees were unemployed, say. The same is true: just because 4/7 of an entire group skis, that doesn't mean 4/7 of some specific subset of that group (the tennis players) will also ski.