I have N different objects and I choose g out of them

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In summary, the conversation discusses the probability of two sets of objects sharing at least one element and exactly one element. The method for calculating the number of ways to choose these sets is explained, and the correct approach is clarified.
  • #1
qasdc
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Hi!
I have the following questions and I would like some help.

I have N different objects and I choose g out of them (without repetition), avoiding permutations of the objects. This can be done in N!/(N-g)!g! ways.
I create another set of g objects in the same way.

So, I have two such sets of g objects and the question is what is the probability that these two sets have at least one object in common? What is the probability of having exactly one object in common?

My actual problem is that i don't count correctly the different ways that I can create two sets with one object i common.

Could anyone please help?
 
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  • #2


Well, the probability that the two sets share at least one element is 1 minus the probability that the sets do not share any elements between them. The number of ways to choose 2 sets of size g each from a set of N objects such that the sets have no intersection can be counted by the following method:
1. Select a set of size 2g from the set of N objects
2. Select a set of size g from the set of size 2g, thus partitioning the 2g elements into two disjoint sets of size g

That should be enough hints to get you going on the first part. For the second part, count the sets that share exactly one element this way:
1. Select one element from the set of size N, to be the shared element
2. Select two disjoint sets each of size g-1 from the set of size N-1, using the method of the first part
 
  • #3


Ok, thnx!

I now understand what was wrong the way I counted.
 

1. What is the formula for calculating the number of combinations when choosing g objects from a set of N objects?

The formula for calculating the number of combinations is nCr = n! / (r! * (n-r)!), where n represents the total number of objects in the set and r represents the number of objects chosen.

2. How does the number of combinations change if the order of the chosen objects does not matter?

If the order of the chosen objects does not matter, then the number of combinations is reduced. The formula for calculating the number of combinations when order does not matter is nCr = n! / (r! * (n-r)!) = (nPr) / r!, where n represents the total number of objects in the set, r represents the number of objects chosen, and nPr represents the number of permutations of n objects taken r at a time.

3. Can you provide an example of choosing g objects from a set of N objects?

Sure, let's say we have a set of 5 different colors: red, blue, green, yellow, and purple. If we want to choose 3 colors from this set, we can find the number of combinations using the formula nCr = n! / (r! * (n-r)!). So, n = 5 and r = 3, giving us 5C3 = 5! / (3! * (5-3)!) = 10. The 10 possible combinations are: red, blue, green; red, blue, yellow; red, blue, purple; red, green, yellow; red, green, purple; red, yellow, purple; blue, green, yellow; blue, green, purple; blue, yellow, purple; green, yellow, purple.

4. How do combinations differ from permutations?

Combinations and permutations are similar in that they both involve selecting objects from a set. However, the main difference is that combinations do not take into account the order of the selected objects, while permutations do. For example, if we have a set of 3 letters: A, B, and C, and we want to choose 2 letters, the combinations would be AB, AC, and BC, while the permutations would be AB, BA, AC, CA, BC, and CB.

5. What is the significance of choosing g objects out of a set of N objects?

The significance of choosing g objects out of a set of N objects depends on the context. In mathematics, combinations are often used in probability and statistics to calculate the likelihood of certain outcomes. In computer science, combinations can be used in algorithms and data structures. In real-life situations, combinations can represent choices or arrangements, such as choosing a team of players from a larger pool or arranging a menu of options.

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