Conditional distribution

In summary, there can be at most 2^(n-1) children attending the Christmas party, with each child receiving at most one present of each type and each subset of presents being unique among the children.
  • #1
nuuskur
Science Advisor
858
914

Homework Statement


Santa has n types of presents. Every child can receive at most one present of each type and:
a) every child has to get a present AND cannot receive the same set of presents as any other child.
b) for every 2 children, there must be a present that both of the children get
How many children can attend the Christmas party at most?

Homework Equations

The Attempt at a Solution


Assuming my interpretation is correct:
Every child getting at most one of each present type - is this a fancy way of saying injection?
All sets of presents have to be different. There are 2n - 1 different sets of presents (we cannot count the empty set since every child has to have a present - we are not concerned if the children do not receive the same number of presents i.e the cardinalities need not be equal).

Per every 2 children, they must have a common present - this is the troublesome bit. What does it mean, exactly?
I am sure it doesn't mean that ALL of the chosen subsets need to have a common element.

This seems to be the attendance limiter - otherwise I can have 2n - 1 people at the party.
 
Physics news on Phys.org
  • #2
Suppose you allocate some (proper) subset of the types to a child. That rules out some other subsets for what can be allocated in future. Having allocated subsets to r children, can you find a lower bound for the number of subsets that have been ruled out?
 
  • #3
If I simplify - assume that there is a child that receives only one present, then by the condition:
Per every 2 child, they must have a common present.

This means that everybody has to have the same gift as the child with one gift.
looks something:
[tex]C_1 = \{x_1\}\\C_2 = \{x_1, x_2\}\\C_3 = \{x_1, x_2, x_3\}[/tex]

I propose that:
if the maximum amount of people are attending, then there is one person who receives one present
there can be Only one person who receives one present.

If there are 2 people who receive one present, then they do not have a common present, because no two sets can be identical and that also violates the next condition.

IF the smallest set of gifts has 2 presents, then there has to be a present xi that is in every set of presents, but then we can have another person at the party who receives the gift xi, therefore if the maximum amount of people are attending, the smallest set of gifts contains one present.

For 2 gifts, if xi is present, there are also n-1 possibilities for the second gift.
For 3 gifts, if xi is present, there are [itex]\binom{n-1}{2}[/itex] possibilities to combine the sets of gifts that contain xi
.
.
Careless mistake - I had written [itex]\sum_{k=0}^n \binom{n-1}{k}[/itex], but after k = n we get error :D

There would be [itex]\sum_{k=0}^{n-1}\binom{n-1}{k} = 2^{n-1}[/itex] possible ways - the maximum amount of people attending.

Now I see an easier way - we must consider the subsets that contain xi - that leaves n-1 types to choose from. The number of subsets of n-1 types is 2n-1
 
Last edited:

1. What is a conditional distribution?

A conditional distribution is a statistical distribution that describes the probability of an event occurring given that another event has already occurred. It is used to model the relationship between two variables and can help us understand the impact of one variable on the other.

2. How is a conditional distribution different from a marginal distribution?

A marginal distribution represents the probability of a single variable occurring, while a conditional distribution takes into account the occurrence of another variable. In other words, a marginal distribution is the overall probability distribution, while a conditional distribution is a subset of that distribution.

3. How is a conditional distribution calculated?

A conditional distribution is calculated by dividing the joint probability of two variables by the marginal probability of the second variable. This can be written as P(A|B) = P(A ∩ B) / P(B), where A and B are two events.

4. What is the purpose of studying conditional distributions?

Studying conditional distributions can help us understand the relationship between two variables and how they impact each other. It can also be used to make predictions and inform decision-making in various fields such as finance, economics, and biology.

5. Can a conditional distribution be used to determine causality?

No, a conditional distribution alone cannot determine causality between two variables. It can only show the relationship and provide insights into the probability of an event occurring, given the occurrence of another event. Additional research and experimentation are needed to establish causality.

Similar threads

  • Precalculus Mathematics Homework Help
Replies
5
Views
2K
Replies
8
Views
546
  • Precalculus Mathematics Homework Help
Replies
7
Views
2K
  • Precalculus Mathematics Homework Help
Replies
8
Views
4K
  • Other Physics Topics
Replies
8
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
6
Views
686
  • Special and General Relativity
Replies
4
Views
727
  • Precalculus Mathematics Homework Help
Replies
3
Views
5K
  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
1K
Replies
90
Views
5K
Back
Top