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Set Theory Proof : Inclusion-Exclusion Principle

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3. This exercise is about the inclusion-exclusion principle.
a) Let X and Y be finite ts and suppose that |X| = 11, |Y| = 6, and
|X∩Y| =4. Find |XUY|.
b) Suppose that U is a finite universal set. If |U| = 21, |XUY| = 11. |X| = 4 and |Y|= 10. find |XcUYc|.
c) Each tile in a collection of 19 is a square or a triangle and is also red or blue. Suppose that 12 of the 19 tiles are squares. 11 are red, and 4 are blue squares. Using the inclusion-exclusion principle, determine:
(1) the number of tile which are square or blue;
(2) the number of tiles which are triangles and red;
(3) the number of tiles which are red or squares.
[Hint: Let U be the (universal) set of all the 19 tiles and let S. T. R, and B denote the subset of tiles which is a square (respectively a triangle, red, and blue). Then T = SC and R = B. Part (2) comes down to computing |T∩R| and part (3) to determining |BcUTc|.

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The Inclusion-Exclusion Principle is investigated.

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Solution.

a)

b) Since , we have

We know that

Note that |U|=21, we have
...

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  • MA, Shandong Univ.
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  • "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
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