1D Random Walk of people meeting

In summary: Using the hint, we can see that these points have higher probabilities of being reached during the walk, increasing the chances of the friends meeting there.
  • #1
frinny913
4
0
Problem: Three friends do a 1D Random Walk with p=q starting at 0. Are they guaranteed to all meet again somewhere? So all the friends are starting at 0 at the same time and we want to know if they are guaranteed to meet again anywhere in the walk.

Hint: if they do meet, which places are likely?

So, so far I have found through calculations that they aren't guaranteed to all meet at zero and that four friends aren't guaranteed to all meet somewhere. The problem with the three people meeting somewhere random is that when i try to use the same technique i used to find if they all meet at 0 or to find if 4 people meet somewhere doesn't work for this one. I also don't really understand how to use his hint.
I have a feeling that the probability of three people meeting anywhere is greater than the probability of three people meeting at 0 but that doesn't really get me far either.
 
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  • #2
Answer: The probability of any three friends meeting at any point of their 1D Random Walk with p=q starting at 0 is not guaranteed, but it is highly likely. The most likely points for them to meet are the origin (0), their respective maximums, and their respective minimums.
 

1. What is a 1D random walk?

A 1D random walk is a mathematical model that describes the movement of a single point or particle along a straight line, where each step is taken at random.

2. How does the "people meeting" aspect factor into a 1D random walk?

In the context of a 1D random walk, the "people meeting" aspect refers to the possibility of two or more points or particles crossing paths at a random point in time.

3. What is the significance of studying 1D random walk of people meeting?

Studying 1D random walk of people meeting can provide insights into various real-world phenomena, such as the spread of diseases, traffic flow, and social interactions.

4. What are some variables that can affect the outcomes of a 1D random walk of people meeting?

Some variables that can affect the outcomes of a 1D random walk of people meeting include the number of people, the distance between them, the probability of them meeting, and the duration of the walk.

5. How is the "meeting" event in a 1D random walk of people meeting modeled?

The "meeting" event in a 1D random walk of people meeting is typically modeled using a probability distribution, such as the binomial distribution, to determine the likelihood of two or more points or particles crossing paths at a given time.

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