Any connection between 3 concepts and probability

In summary, the conversation discusses the problem of finding the probability of getting a particular sum by rolling multiple six-sided dice at the same time. It is suggested that there is a connection between polynomials, Pascal's triangle, combinations, and dice that can help solve this problem. Specifically, by considering the polynomial expansion of (1+x+x^2+x^3+x^4+x^5)^5, where each term represents a possible dice score and the exponent corresponds to the number of dice rolled. This concept is further explained through the use of probability-generating functions.
  • #1
davedave
50
0
I have posted a similar problem not long ago.This time, I am trying to find a connection between 3 concepts that would possibly lead to the answer to the problem.

I have heard that there is a way to find the probability of getting a particular sum by rolling multiple six-sided dice at the same time without listing ALL the outcomes which is really horrifying.

Someone told me that there is a connection among polynomials, Pascal's triangle, combinations and dice.

For example, say you roll 5 six-sided fair dice and want to find the probability of getting a sum of 17. In this case, there are 780 combinations of such a sum and 6^5 different sums.
So, the probability of the sum of 17 is 0.100308641975309.

That person said that you consider the polynomial expansion of
(1+x+x^2+x^3+x^4+x^5)^5 .

Each term is raised to ascending powers. The 6 terms in there represent the 6 sides of each die and the 5th power represents the 5 dice. If you can connect it to Pascal's triangle and combinations, you will get the correct answer as stated above.

I am not sure if I wrote down the polynomial correctly. I lost contact with that person.

Can someone tell me how it is possible to solve the 5 six-sided dice problem with those concepts? Thanks.
 
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  • #2
davedave said:
... you consider the polynomial expansion of
(1+x+x^2+x^3+x^4+x^5)^5

It might be easier to work with (x+x^2+...+x^6)^5. That way the exponent of x corresponds to the dice score and the coefficient is the number of possible ways of getting that score. If you're not sure, try the examples with 1 dice and 2 dice by hand to convince yourself that it works. Does that help?
 
  • #3
You should take a look on the concept of "probability-generating function".
 

What is the relationship between probability and scientific concepts?

The concept of probability is a mathematical measure of the likelihood of an event occurring. In science, probability is often used to describe the chances of a particular outcome or result in an experiment or observation. Scientists use probability to make predictions, analyze data, and draw conclusions about their research.

How can probability be used to understand complex scientific concepts?

Probability can be used to understand complex scientific concepts by providing a quantitative measure of uncertainty. It allows scientists to assign a numerical value to the likelihood of certain outcomes or events, making it easier to compare and analyze different scenarios. This can help scientists make informed decisions and draw more accurate conclusions based on the data.

Can probability be used to make predictions about scientific phenomena?

Yes, probability can be used to make predictions about scientific phenomena. By analyzing data and using mathematical models, scientists can calculate the likelihood of certain outcomes or events occurring. This can help them make predictions about future observations or experiments and test the validity of their theories.

Are there any limitations to using probability in scientific research?

While probability is a useful tool in scientific research, it is important to note its limitations. Probability can only provide an estimate of the likelihood of an event, and it cannot guarantee a specific outcome. Additionally, probability relies on the assumption that all possible outcomes are equally likely, which may not always be the case in real-world situations.

How can scientists ensure the accuracy of their probability-based predictions?

To ensure the accuracy of their probability-based predictions, scientists must carefully design their experiments and collect data from a large and diverse sample. They must also use appropriate statistical methods to analyze the data and account for any potential biases. Additionally, scientists should continuously review and refine their predictions as new data and information become available.

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