Questions   
Sort: 
 #9
avatar+118659 
0
Apr 18, 2022
 #5
avatar+2489 
+1

Solutions:

 

The easiest method to solve this (IMHO) is to note there are (6^5) unique arrangements of five (5) dice, and each with 1 to 6 pips. Reserve two of these dice and populate them with (1, 2) and (2, 1). Populate the remaining three spaces with dice populated with 3 to six pips. Divide this by the total population sample.  

 

\(\large nPr(5,2) \normalsize* \dfrac{4^3}{6^5} = 0.164609\)

 

Note this is a permutation of a set of 2 from 5. (A combination will only count the sets). This counts both the sets and their order; that is there are 10 set of (1, 2) and 10 sets of (2, 1) for a total of 20 unique sets. With 2 spaces for two of the dice counted and populated with (1, 2) and (2, 1), the 1’s and 2’s are removed from the remaining sample space giving (4^3). The product of (nPr(5,2) * 4^3 = 1280) gives the number of sets of five with a single “1”and a single “2” in each set. Dividing this by 6^5 gives the probability that a roll of five dice will produce one of these sets.

 

This method works for any selection of fixed dice with any population size.

----------------

 

Other solutions:

 

Changing CPhill’s equation (C (5,2) * (1/6)^2 * (4/6)^3) to a permutation, presents the correct solution probability.  nPr (5,2) * (1/6)^2 * (4/6)^3 = 0.164609. This equation resembles a binomial probability with a missing fraction....kinda like an overly-close circumcision.  Note that the exponent (2) corresponds to the (r) and the sum of the exponents (5) corresponds to the (n). Why does this work?  IDK... This is a Nancy Drew mystery, and Gingerlock Holms has yet to solve it.

 

Best guess: The asymmetry of probability is corrected in the permutations. This equation will work for any (n) when (r=2), with corresponding adjustments to the exponents. It does not work when (r>2).

 

GA

 --. .-

Apr 18, 2022
Apr 17, 2022

0 Online Users