Math Problem Statement

To solve this problem, we need to determine the probability that four randomly generated subsets of ({1, 2, 3, 4, 5}) have no elements in common and their union is ({1, 2, 3, 4, 5}).

Total Subsets: Each subset of ({1, 2, 3, 4, 5}) can be any of the (2^5 = 32) subsets. Since Tom presses the button 4 times, there are (32^4) possible outcomes.

Valid Subsets: We need to count the number of ways to choose four subsets such that:

Each element of ({1, 2, 3, 4, 5}) appears in exactly one of the four subsets.

No element is repeated in any subset.

Distribution of Elements: We can think of distributing the 5 elements into 4 distinct subsets. This is equivalent to finding the number of surjective (onto) functions from a set of 5 elements to a set of 4 elements.

Counting Surjective Functions: The number of surjective functions from a set of size (n) to a set of size (k) is given by:

k!⋅S(n,k)

where (S(n, k)) is the Stirling number of the second kind, representing the number of ways to partition (n) elements into (k) non-empty subsets.

For (n = 5) and (k = 4):

S(5,4)=10

Therefore, the number of surjective functions is:

4!⋅S(5,4)=24⋅10=240

Probability Calculation: The probability (P) that the four subsets have no elements in common and their union is ({1, 2, 3, 4, 5}) is:

P=324240​=1048576240​=6553615​

Finding (p + q): The irreducible fraction is (\frac{15}{65536}), so (p = 65536) and (q = 15). Therefore, (p + q = 65536 + 15 = 65551).

So, (p + q) is 65551.rm with this

Solution

The problem you’ve laid out involves determining the probability that four randomly generated subsets of the set S={1,2,3,4,5}S = \{1, 2, 3, 4, 5\} have no elements in common, and their union covers the entire set SS.

Let’s walk through the solution step by step:

Step 1: Total Number of Possible Subsets

Each subset of SS can be any subset of SS, so the total number of subsets of SS is: 25=322^5 = 32 Since we are pressing the button 4 times, the total number of possible outcomes is: 324=104857632^4 = 1048576 This is the total number of ways to randomly select four subsets from SS, with each subset having 32 possibilities.

Step 2: Counting Valid Subsets

We are tasked with ensuring that:

  1. The union of the four subsets covers all the elements in SS.
  2. No element is repeated in any subset (i.e., no element of SS appears in more than one subset).

This problem can be viewed as distributing the 5 elements of SS into 4 distinct subsets, with each element going to exactly one subset. This is equivalent to finding the number of surjective (onto) functions from a set of 5 elements to a set of 4 distinct subsets.

Step 3: Surjective Function Calculation

The number of surjective functions from a set of size nn to a set of size kk is given by: k!S(n,k)k! \cdot S(n, k) where S(n,k)S(n, k) is the Stirling number of the second kind, which counts the number of ways to partition nn elements into kk non-empty subsets.

For n=5n = 5 and k=4k = 4, the Stirling number S(5,4)S(5, 4) is 10, meaning there are 10 ways to partition the set of 5 elements into 4 non-empty subsets. Thus, the number of surjective functions is: 4!S(5,4)=2410=2404! \cdot S(5, 4) = 24 \cdot 10 = 240 This gives us the number of valid ways to assign each element of SS to one of the four subsets such that no subset is empty and no element appears in more than one subset.

Step 4: Probability Calculation

The probability PP that the four randomly generated subsets have no elements in common and their union is SS is: P=Valid SubsetsTotal Subsets=2401048576=1565536P = \frac{\text{Valid Subsets}}{\text{Total Subsets}} = \frac{240}{1048576} = \frac{15}{65536}

Step 5: Finding p+qp + q

The irreducible fraction for the probability is 1565536\frac{15}{65536}, where p=65536p = 65536 and q=15q = 15. Therefore: p+q=65536+15=65551p + q = 65536 + 15 = 65551

Thus, the final answer is 65551.

Would you like more details or have any questions about this solution?

Further Questions:

  1. How do Stirling numbers of the second kind relate to partitioning sets?
  2. How can you generalize this problem for different set sizes?
  3. What is the significance of surjective functions in combinatorics?
  4. How does the probability change if we increase the number of subsets?
  5. What are other examples of problems involving partitioning sets?

Tip:

When dealing with set partitions and surjective functions, Stirling numbers of the second kind are a powerful tool for counting the ways to assign elements into distinct non-empty subsets.

Ask a new question for Free

By Image

Drop file here or Click Here to upload

Math Problem Analysis

Mathematical Concepts

Combinatorics
Set Theory
Probability

Formulas

Total subsets: 2^n
Surjective function formula: k! ⋅ S(n, k)
Probability formula: P = Valid Subsets / Total Subsets

Theorems

Stirling numbers of the second kind
Surjective functions in combinatorics

Suitable Grade Level

Undergraduate level (Combinatorics)