How Many Hats Must Be Sampled to Guarantee Every Color Is Included?

AI Thread Summary
To ensure that every color of hat is represented in a sample from a set of 400 hats with six colors, a mathematical approach is needed. The discussion suggests calculating the minimum number of samples required to achieve a probability greater than 0.9 of including all colors. The hint indicates that one can first determine how many hats must be drawn to cover all colors except one (yellow) and then draw one additional hat. This problem involves combinatorial probability and may require complex calculations to derive the exact minimum number of samples needed. Ultimately, the goal is to find a sampling strategy that guarantees representation of all hat colors.
neutrino71
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In a set of 400 hats, each hat is represented by one of six colors (brown, pink, red, orange, blue, yellow). You may assume that each color is represented rather equally in the 400 hats.
What is the minimum amount of samples we must take to be likely to have a sample which has a hat of every color?
 
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"likely" is rather qualitative. If can quantify it, say P>0.9, then an answer can be obtained, although the calculation may be a little messy.
 
neutrino: do you have any thoughts about how you might start this problem?
 
neutrino71 said:
In a set of 400 hats, each hat is represented by one of six colors (brown, pink, red, orange, blue, yellow). You may assume that each color is represented rather equally in the 400 hats.
What is the minimum amount of samples we must take to be likely to have a sample which has a hat of every color?
what minimum # of hats must be drawn (without replacement) to have probability 1 of having each hat color represented at least once (if each color is "rather equally represented" in the original set of 400 hats)?
(hint: what minimum # must be drawn to use up all colors except yellow, then choose 1 more.)
 
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