Statistics: Polls and probability

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SUMMARY

The discussion focuses on calculating the probability of a fictive proposition A passing based on a poll of 1000 respondents, where 480 indicated they would vote "yes." The formula used is derived from binomial probability, specifically P = (n + 1)! / (m!(n - m)!) f^m (1 - f)^(n - m). Participants suggest using the normal approximation to estimate the probability of more than 50% voting "yes," which involves the expression P ∝ exp(-n((f - f0)^2) / (2f0(1 - f0))). The conversation emphasizes the need for a proper approach to transition from discrete to continuous distributions.

PREREQUISITES
  • Understanding of binomial probability and its formulas
  • Familiarity with normal approximation techniques in statistics
  • Knowledge of discrete versus continuous probability distributions
  • Basic concepts of polling and voting probability calculations
NEXT STEPS
  • Study the application of the Central Limit Theorem in polling scenarios
  • Learn about the continuity correction in normal approximations
  • Explore advanced statistical methods for estimating probabilities in discrete distributions
  • Investigate the implications of sample size on polling accuracy and confidence intervals
USEFUL FOR

Statisticians, data analysts, students studying probability theory, and anyone involved in polling and survey analysis will benefit from this discussion.

Niles
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Homework Statement


Hi all.

At a poll in America, where 1000 people have been asked, 480 people said that they would vote yes on proposition A (it is a fictive proposition), and of course 520 people said they would vote no on proposition A.

I have to find the probability that proposition A will pass.

What I have done is to use the following formula:

[tex] P = \frac{{(n + 1)!}}{{m!(n - m)!}}f^m (1 - f)^{n - m},[/tex]

which has been derived in class. Here m is 480, n is 1000. P is the probability of M persons answering "yes" out of N total (so N is the total amount of people in America voting, and M is the amount in America that votes "yes") when we have a sample of n (1000), where m (480) have answered "yes". f is equal to M/N.

My attempt is that if more than 50% vote yes, then prop. A will pass. So I want to integrate P from N/2 to N, but it is not a continuous distribution. I thought of finding P for N/2 (i.e. that 50% will answer "yes"), but that is only the probability of 50% answering yes, and does not include the rest from > 50%.

What would be the most proper approach to this problem?

Thanks in advance.
 
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The proposition will pass if at least 50% of the voters vote for it, so your basic idea is correct.
Try the normal approximation to find the probability you need.
 
Hi statdad

Thanks for replying. The normal approximation gives us:

[tex] P \propto \exp \left( { - n\frac{{(f - f_0 )^2 }}{{2f_0 (1 - f_0 )}}} \right),[/tex]

where f0 is the mean, i.e. m/n. This is still a discrete distribution, so what is the next step from here?

Thanks in advance.
 

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