Probability of rearrangements of letters

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In summary, the probability of rearrangements of letters refers to the likelihood of a set of letters being rearranged in different ways. It is calculated using the permutation formula and has real-life applications in password cracking and games like Scrabble. The length of the set of letters affects the probability, with longer sets having a higher probability. This concept is also significant in scientific fields, such as genetics and statistical analysis.
  • #1
UniPhysics90
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If the letters of the word 'MINIMUM' are arranged in a line at random, what is the probability that the 3 M's are together at the beginning of the arrangement.

There are 2 methods outlined to solve this problem.

Method 1: (3/7)*(2/6)*(1/5)=(1/35) I understand this method completely.

The method I would like clarified is:

Method 2:

The statistical weight, w, w=7!/(3!2!1!1!)=420.
The number of ways of writing 'mmm****' where * is (i,n,u) is 4!/(2!1!1!)=12.
Thus p=12/420=1/35I get that the factorials are used as m is repeated 3 times, and i 2 times. I don't know why we divide by these, as in my mind there are 7! possible ways of arranging the letters, albeit some of them repeats. For probability, why is this used? Thanks
 
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  • #2
UniPhysics90 said:
If the letters of the word 'MINIMUM' are arranged in a line at random, what is the probability that the 3 M's are together at the beginning of the arrangement.

There are 2 methods outlined to solve this problem.

Method 1: (3/7)*(2/6)*(1/5)=(1/35) I understand this method completely.

The method I would like clarified is:

Method 2:

The statistical weight, w, w=7!/(3!2!1!1!)=420.
The number of ways of writing 'mmm****' where * is (i,n,u) is 4!/(2!1!1!)=12.
Thus p=12/420=1/35


I get that the factorials are used as m is repeated 3 times, and i 2 times. I don't know why we divide by these, as in my mind there are 7! possible ways of arranging the letters, albeit some of them repeats. For probability, why is this used? Thanks

The reason for calculating w is to count the number of possible arrangements of the letters in MINIMUM, all of which we assume to be equally likely. If all the letters were distinct, the number of arrangements would be 7!. But there are duplicates: 3 Ms, 2 Is. So imagine we put tags on the Ms and Is and consider the set [tex]\{M_1, I_1, N, I_2, M_2, U, M_3\}[/tex]. With the tags, there are now 7! arrangements. Now divide by 3! to compensate for the fact that the Ms are actually indistinguishable and divide by 2! to compensate for the fact that the Is as indistinguishable.

Does this make sense to you? It may help to know that the numbers you are calculating are multinomial coefficents: see

http://en.wikipedia.org/wiki/Multinomial_coefficient
 
  • #3
Here are two slightly different versions of your method 2:

(a) Suppose the letters were written on 7 balls in a bag.
There are 7! possible ways to draw the balls from the bag (but not every way looks different, because there are 3 M's and 2 I's)

The number of ways to draw the 3 Ms, followed by the 4 other letters, is
3! 4!

So the probability is 3! 4! / 7! = 1/35

(b). Now, suppose you are writing the letters in a line.
The number of diifferent ways to write the 7 letters is 7! / 2! 3! (because there are 3 Ms and 2 Is)
The number of different ways to write 3 Ms followed by the other 4 letters is
1 (for the 3 Ms) x 4!/2! (for the other four letters, includng the two I's)

So the probabilty is
(4!/2!) / (7!/2!3!)
= 2! 3! 4! / 2! 7! = 1/35

Hope that helps.
 
  • #4
awkward said:
The reason for calculating w is to count the number of possible arrangements of the letters in MINIMUM, all of which we assume to be equally likely. If all the letters were distinct, the number of arrangements would be 7!. But there are duplicates: 3 Ms, 2 Is. So imagine we put tags on the Ms and Is and consider the set [tex]\{M_1, I_1, N, I_2, M_2, U, M_3\}[/tex]. With the tags, there are now 7! arrangements. Now divide by 3! to compensate for the fact that the Ms are actually indistinguishable and divide by 2! to compensate for the fact that the Is as indistinguishable.

Does this make sense to you? It may help to know that the numbers you are calculating are multinomial coefficents: see

http://en.wikipedia.org/wiki/Multinomial_coefficient

The idea makes sense, in terms of number of different rearrangements. But if there are multiple of the same letter, does this not increase the probability of getting that combination?

ie m(1),m(2),m(3)i(1)n(1)i(2)u(1) is the same arrangement in terms of just letters as m(2),m(1),m(3)i(1)n(1)i(2)u(1) etc.
 
  • #5
UniPhysics90 said:
But if there are multiple of the same letter, does this not increase the probability of getting that combination?

No, because you can divide all of the 7! possible arrangements into groups of 3! 2! arrangements where the Ms and Is are in the same position for all the arrangements in the group.

Each group contains the same number of arrangements, so you can either count the number of groups, or count the total number of arrangements. My previous post did it both ways.
 

What is the "Probability of rearrangements of letters"?

The probability of rearrangements of letters refers to the likelihood that a set of letters or characters can be rearranged in different ways. This concept is often used in mathematics and computer science to calculate the number of possible arrangements of a given set of letters.

How is the probability of rearrangements of letters calculated?

The probability of rearrangements of letters can be calculated using the formula n! / (n1! * n2! * ... * nk!), where n is the total number of letters and n1, n2, ..., nk are the number of times each letter appears in the set. This formula is known as the "permutation formula".

What are some real-life examples of the probability of rearrangements of letters?

One real-life example of the probability of rearrangements of letters is in password cracking. Hackers use algorithms to calculate the probability of different combinations of letters and numbers in order to guess someone's password. Another example is in Scrabble, where players calculate the probability of different letter combinations in order to strategize their moves.

How does the length of the set of letters affect the probability of rearrangements?

The longer the set of letters, the higher the probability of rearrangements. This is because with more letters, there are more possible combinations and permutations. For example, the probability of rearrangements for a set of 5 letters is higher than for a set of 3 letters.

What is the significance of the probability of rearrangements of letters in science and research?

The probability of rearrangements of letters is important in a variety of scientific fields, such as genetics, where it is used to calculate the likelihood of certain genetic traits being passed down from parents to offspring. It is also used in statistical analysis to understand the likelihood of certain outcomes in experiments and studies.

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