Binomial Distribution for a person walking in straight line

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The discussion revolves around using the binomial distribution to calculate the probability of a person ending up at a specific location after taking n steps, with different probabilities for moving in two directions. The participant questions whether the binomial distribution can be applied when the steps involve larger distances, specifically moving x=x+3 with probability p and x=x-1 with probability q. Clarifications are made regarding the calculation of probabilities based on the number of steps taken in each direction and the importance of correctly substituting values into the binomial expression. There is also a suggestion to use shorthand notation for binomial coefficients for simplicity. The conversation emphasizes the need for careful mathematical formulation in probability calculations.
CourtneyS
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Homework Statement


Can I measure the probability of a person being at a certain end location after n steps using the binomial distribution if,
probability student goes x=x+3 is 0 <= p <0.5 , x=x-1 is 0<= 0.5 p <1.

Homework Equations


x=x+3 is 0 <= p <0.5
x=x-1 is 0<= 0.5 p <1

The Attempt at a Solution


I know that I can do this for x=x+1 0<=p<0.5 and x=x-1 0.5<=p<1
And I know it doesn't work if it's position based, so for example at x=10, the probabilities changed.
But, can I do it if they move a larger distance in one direction than the other such as the example I have posted?
Thanks
 
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CourtneyS said:

Homework Statement


Can I measure the probability of a person being at a certain end location after n steps using the binomial distribution if,
probability student goes x=x+3 is 0 <= p <0.5 , x=x-1 is 0<= 0.5 p <1.

Homework Equations


x=x+3 is 0 <= p <0.5
x=x-1 is 0<= 0.5 p <1

The Attempt at a Solution


I know that I can do this for x=x+1 0<=p<0.5 and x=x-1 0.5<=p<1
And I know it doesn't work if it's position based, so for example at x=10, the probabilities changed.
But, can I do it if they move a larger distance in one direction than the other such as the example I have posted?
Thanks

I think you meant to say that the moves are ##x \to x+3## w.p. ##p## and ##x \to x-1## w.p. ##q = 1-p##; here ##0 < p < 1/2##. (The case ##p=0## should be excluded, because it is trivial---there is no randomness at all.)

After ##n## steps, if the student takes ##k## steps to the right and ##(n-k)## steps to the left, how far to the right has he/she moved? (Of course, a negative distance to the right is a positive distance to the left.)

I did not understand at all the rest of your post, where you talk about x = 10 and larger distances, etc.
 
Last edited:
Can I say that probability for any given end point x, the probability of ending up there is :
probability = {factorial(n)/(factorial((n+(x+3))/2)*factorial((n-(x-1))/2))}*{p^(1/2(n+(x+3)) * q^(1/2(n+(x-1)))}
Where p = probability of moving x+3 and q = 1-p
 
CourtneyS said:
Can I say that probability for any given end point x, the probability of ending up there is :
probability = {factorial(n)/(factorial((n+(x+3))/2)*factorial((n-(x-1))/2))}*{p^(1/2(n+(x+3)) * q^(1/2(n+(x-1)))}
Where p = probability of moving x+3 and q = 1-p

That is not what I get. Just solve for ##k## in terms of ##x## and substitute that into the binomial expression, but do it carefully. (Of course, I assume the starting point is ##x = 0##).

BTW: it is normal in probability to use shorthand notation for binomial coefficients: instead of
\frac{a!}{b! (a-b)!}
we usually write
\binom{a}{b} \;\;\rm{or} \;\; C(a,b) \;\; \rm{or} \;\; {}_aC_b
Of course, when we actually want to compute the binomial coefficient, we fall back on the original formula in terms of factorials. However, do what makes you most comfortable; I am just offering advice that you can take or leave.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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