Time: 2 weeks
Team: 2
Language: Python
Several months before an important election, many polls seem to pop up from nowhere. Their interpretations are often surrounded by uncertainty: to what extent are these polls reliable? Why are there so many differences between poll institutes? And from day to day? Is a 3% variation significant? etc...
To estimate the accuracy of the results, a confidence interval is given. It is defined by the fact that there is a x% probability that this interval encompasses the true value.
You already know that questioning people follows a Bernoulli process, and therefore that a binomial distribution (converging toward a normal distribution) is a good model for the results. You can then easily compute the confidence intervals, knowing that:
- The 95% confidence interval amplitude is
2 × 1.96√v - The 99% confidence interval amplitude is
2×2.58√v
where v stands for the variance of the sample proportion (corrected for finite populations).
The goal of this project is to compute the 95% and 99% confidence intervals.
>> ./209poll -h
USAGE
./209poll pSize sSize p
DESCRIPTION
pSize size of the populations
Size size of the sample (supposed to be representative)
p percentage of voting intentions for a specific candidate
Author Corentin COUTRET-ROZET and PATRICIA MONFA-MATAS