Combinatorial argument probabilities

In summary: Now, let's look at the questions posed in the problem. Question 1 is asking us to find the number of possible outcomes, or the total number of ways we could get a maximum value from the k+1 drawings. This is given by |Ω|, which we established earlier is equal to nk+1.Question 2 is asking us to express Ω, or the set of all possible outcomes, in terms of the individual events E1, E2, E
  • #1
Dassinia
144
0
Hello
1. Homework Statement

Consider fk N*→N, k≥0
fk(n)=Σ jk n>0

We're looking to establish these identities, using a combinatorial argument
fk(n)=n if k=0
fk(n)= 1/(k+1) [ nk+1 + Σ ( i , k+1) (-1)k+1-ifi(n) ] if k>0
the sum is about i from i=0 to i=k-1 and (i, k+1) is the combination.

Consider the experience of k+1 drawing with handoff from a box of n balls numbered
Ej : the maximum of the values obtained on the k+1 draw is j , j=1,...,n
Fj : The drawing are made on {1,...,j} j=1,...,n
Fo=
vide.gif


1. Find |Ω|
2. Write Ω as an operation on sets E1,...,En
3. Write Ej as an operation on sets Fj-1, Fj j=1...n
4. Find |Fj| j=0...n
5. Find |Ej| j=1...n
6. Find |Ω| through the calculation of |Ej| j=1...n and using the binomial theorem

Homework Equations


(x+y)n=∑(k, n)xn-kyk

The Attempt at a Solution



1. |Ω|=nk+1
2. Ω=∩ Ej for j=1,...,n
3. I just don't get what Fj represents..? :oldconfused:

Thanks
 
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  • #2
for posting this interesting problem! I am a scientist and I would be happy to help you with your questions.

First, let's define some terms so we are all on the same page. In this problem, we are looking at a box of n balls, each with a unique number on it. We are also considering k+1 drawings from this box, where each drawing involves randomly selecting one ball from the box and recording the number on it. So, for example, if we have a box with 5 balls numbered 1, 2, 3, 4, and 5, and we make 3 drawings, we might get the following results: 1, 4, 2.

Now, let's take a look at the expressions given in the problem. The first one, fk(n)=n if k=0, is pretty straightforward. This is saying that if we make 0 drawings (k=0), then the maximum value we can get is just n, which is the number of balls in the box.

The second expression, fk(n)= 1/(k+1) [ nk+1 + Σ ( i , k+1) (-1)k+1-ifi(n) ] if k>0, is a little more complicated. But essentially, it is saying that if we make k+1 drawings (k>0), then the maximum value we can get is either the highest number on the ball (nk+1) or the sum of all the possible combinations of numbers we could get (the Σ term). The (-1)k+1 term is accounting for the fact that we are subtracting the sum of all the possible combinations, since we only want the maximum value. The i term represents the number of balls we are choosing from in each combination, and the fi(n) term represents the number of ways we can get that particular combination. For example, if we make 2 drawings (k=1) from a box of 5 balls (n=5), then the maximum value we can get is either 5 (nk+1) or the sum of all the possible combinations of 2 balls (the Σ term). This would be 5 + (-1)^1*f2(5) = 5 + (-1)*10 = -5. So, fk(n)= 1/(k+1) [ nk+1 + Σ ( i , k+1
 

1. What is combinatorial argument probabilities?

Combinatorial argument probabilities refer to the mathematical techniques used to calculate the probability of certain outcomes in a given situation.

2. How is combinatorial argument probabilities different from other types of probabilities?

Unlike other types of probabilities that rely on statistical data, combinatorial argument probabilities use mathematical reasoning and counting techniques to determine the likelihood of certain events.

3. What are some examples of combinatorial argument probabilities?

Some examples include calculating the probability of getting a certain hand in a game of cards, the chances of winning a lottery, or the likelihood of certain genetic traits being passed down from parents to offspring.

4. What are the main principles of combinatorial argument probabilities?

The main principles include the multiplication rule, addition rule, and the principle of inclusion and exclusion, which are used to calculate the number of possible outcomes and their probabilities.

5. How are combinatorial argument probabilities used in real-life situations?

Combinatorial argument probabilities are used in various fields such as finance, economics, biology, and computer science to make predictions and inform decision-making. For example, they can be used to determine the optimal strategy in a game or to assess the risk of a certain investment.

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