Markov chain, sum of N dice rolls

In summary, the problem is asking to prove that Xn, the maximum score obtained after n throws of a fair dice, is a Markov chain. The transition matrix for this Markov chain would have diagonal entries of 1/6, 2/6, 3/6, 4/6, 5/6, 6/6 respectively and would not be a function of n. The state of the process at step n is the maximum of the previous rolls, not the sum of the rolls.
  • #1
simba_
19
0
Question : Let Xn be the maximum score obtained after n throws of a fair dice

a) Prove that Xn is a markov chain and write down the transition matrix

Im having a problem starting the transition matrix

im assuming the states are meant to be the sum. then do you write out the transition matrix for the first 2 throws and have this matrix to the power of n-1?
 
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  • #2
simba_ said:
im assuming the states are meant to be the sum

I suppose if you are studying markov chains with an infinite number of states, you could try interpreting "maximum score" to mean some sort of sum. However, it seems to me that the problem intends the state of the process on the nth roll to be [itex] max \{ R_1,R_2,...R_n\} [/itex] and not [itex] R_1 + R_2 + ... + R_n [/itex]. So if make 3 rolls and they are {3,5,4} the state of the process is [itex] X_3 = 5 [/itex]
 
  • #3
Thanks for your reply, that makes sense.

So the transition matrix is an upper triangular matrix to the power of n-1 with the diagonal entries 1/6, 2/6, 3/6, 4/6, 5/6, 6/6 respectively?
 
  • #4
simba_ said:
So the transition matrix is an upper triangular matrix to the power of n-1
That is incorrect terminology. To compute things about the state at step n in the process, one may raise the transition matrix to a power, but the transition matrix itself, in simple examples, is not a function of n.

with the diagonal entries 1/6, 2/6, 3/6, 4/6, 5/6, 6/6 respectively?

Yes.
 
  • #5
Thank you for your help
 

Related to Markov chain, sum of N dice rolls

What is a Markov chain?

A Markov chain is a mathematical concept that describes a sequence of events in which the probability of each event depends only on the state of the previous event. It is commonly used to model various real-world phenomena, such as stock prices, weather patterns, and game outcomes.

How is a Markov chain related to the sum of N dice rolls?

In the context of dice rolls, a Markov chain can be used to determine the probability of obtaining a certain sum after rolling N number of dice. Each state in the chain represents a possible sum, and the probabilities of transitioning from one state to another are based on the probabilities of rolling certain numbers on the dice.

What is the formula for calculating the probability of a certain sum in N dice rolls?

The formula for calculating the probability of a certain sum in N dice rolls is P(sum = s) = (N choose (s-N)) * (1/6)^s * (5/6)^(N-s), where s is the desired sum and N is the number of dice rolls. This formula is based on the binomial distribution.

Can a Markov chain be used to predict the outcome of future dice rolls?

No, a Markov chain can only be used to calculate the probability of obtaining a certain sum after rolling N dice. It cannot predict the exact outcome of future dice rolls, as each roll is still a random event and is not influenced by previous rolls.

What are some real-life applications of Markov chains and the sum of N dice rolls?

Markov chains and the sum of N dice rolls can be used in various fields, such as statistics, economics, and game theory. They can also be applied to analyze stock market trends, determine optimal betting strategies in gambling games, and predict the likelihood of certain weather patterns.

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