Geometric Distribution problem

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To find the largest value y0 such that P(Y > y0) ≥ .1 for a geometric distribution with a success probability of .3, it's more effective to work from the complementary probability. The goal is to determine y0 such that P(Y < y0) < .9, leading to a finite geometric series. The correct formulation involves the partial sum of the series, which should yield the inequality 1 - (0.7)^(y0) < 0.9. This simplifies to finding y0 where (0.7)^(y0) > 0.1, allowing for the calculation of y0 directly. The discussion highlights the importance of correctly applying the geometric series formula to solve the problem effectively.
FaradayLaws
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Question:
If Y has a geometric distribution with success probability .3, what is the largest value, y0, such
that P(Y > y0) ≥ .1?

Attempt:
So i represented the probability of the random variable as a summation

Sum from y0= y0+1 to infinity q^(yo+1)-1 p ≥ .1
using a change of variables i let l = y0+1

p Sum from y0=l to inf (q)^l-1 ≥ .1

from here I'm stuck.. i was thinking of applying the partial sum for the geometric series but I'm not sure how to proceed from here.


Thanks!
 
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It is easier to work from the other end. Find max y0 such that P(Y < y0) < .9. You will then have a finite sum (geometric series) to work with.
 
oh okay;

once working with the other end =>

summation from y0 =0 to y0-1 of q^y0-1 p < 0.9

with the change of variables l= y0-1

summation from l=0 to l of q^l p < 0.9

now finding the partial sum of the geometric series

p/(1-q) < 0.9
0.3/ 0.3 < 0.9

i'm stuck here ? how do i get the value for y0 ?
 
Your partial sum doesn't look right. It should be a function of y0. It should be something like 1-.3^(y0) < .9. (I am not sure whether it should be y0 or y0+1).
 
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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