Probability/Combinatorics Question

  • Thread starter laz0r
  • Start date
In summary, the NHL currently has 30 teams divided into 4 divisions, and the new commissioner wants to randomly assign them to the divisions while keeping the number of teams in each division the same. This can be done in (30!)/(7!7!8!8!) ways by sequentially assigning teams to each division.
  • #1
laz0r
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Homework Statement



The NHL currently has a total of 30 teams in 4 divisions (7 teams in the Pacific
Division, 7 in the Central Division, 8 in the Metropolitan Division, and 8 in the
Atlantic Division). Suppose the NHL gets a new commissioner, and they have
the curious notion of reshuffling teams by randomly assigning the 30 teams to the
divisions (leaving the number of teams in each division the same as above). How
many different ways can this be done?

Homework Equations



None.

The Attempt at a Solution



There are 30 teams and they must be partitioned into teams of 7, 7, 8, 8, which represent the four divisions..

[tex] (30!)/(7!7!8!8!) [/tex] using a partitioning rule..

I'm not sure if this is the right way to go about it, any hints would be appreciated.
 
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  • #2
laz0r said:

Homework Statement



The NHL currently has a total of 30 teams in 4 divisions (7 teams in the Pacific
Division, 7 in the Central Division, 8 in the Metropolitan Division, and 8 in the
Atlantic Division). Suppose the NHL gets a new commissioner, and they have
the curious notion of reshuffling teams by randomly assigning the 30 teams to the
divisions (leaving the number of teams in each division the same as above). How
many different ways can this be done?

Homework Equations



None.

The Attempt at a Solution



There are 30 teams and they must be partitioned into teams of 7, 7, 8, 8, which represent the four divisions..

[tex] (30!)/(7!7!8!8!) [/tex] using a partitioning rule..

I'm not sure if this is the right way to go about it, any hints would be appreciated.

Sure, and to convince yourself you can do it sequentially. Call the divisions 1--4. In how many distinct ways can you assign teams to division 1? (That is, we pick the 7 to go into division 1 and the remaining 23 go into non-1.) For each distinct division-1 assignment, in how many different ways can we assign 7 to division 2? (That is, of the 23 still left, we assign 7 to division 2 and the other 16 to not [1 or 2].) The first division can be picked in
[tex] N_1 = \binom{30}{7} = \frac{30!}{7! \; 23!} [/tex]
different ways. For each such assignment the second division can be picked in
[tex] N_2 = \binom{23}{7} = \frac{23!}{7! \; 16!} [/tex]
different ways. Together, divisions 1 and 2 can be assigned in
[tex] N_{12} = N_1 \: N_2 = \frac{30!}{7! \; 23!} \cdot \frac{23!}{7! \; 16!}
= \frac{30!}{ 7! \; 7! \; 16!} [/tex]
different ways. Keep going like that until all divisions have been assigned, and you will get your suggested solution.
 
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  • #3
Thanks for the reassurance, I appreciate it. I don't have much experience in the math stats setting as I recently switched into the Statistics major, but I think I'm getting the hang of it.
 

FAQ: Probability/Combinatorics Question

What is probability?

Probability is a branch of mathematics that deals with the likelihood or chance of an event occurring. It is represented by a number between 0 and 1, where 0 means the event is impossible and 1 means the event is certain.

How is probability calculated?

Probability is calculated by dividing the number of favorable outcomes by the total number of possible outcomes. This is known as the probability formula: P(A) = Number of favorable outcomes / Total number of possible outcomes.

What is the difference between theoretical and experimental probability?

Theoretical probability is based on mathematical calculations and assumes that all outcomes are equally likely. Experimental probability is based on actual data from experiments or observations and can vary from the theoretical probability.

What is the difference between permutation and combination?

Permutation is the arrangement of a set of objects in a specific order, while combination is the selection of a subset of objects from a larger set without regard to order.

How can probability be used in real-life situations?

Probability can be used in real-life situations to make predictions or decisions based on the likelihood of an event occurring. It can be used in areas such as finance, insurance, and risk assessment.

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