The right answer is: E, according to the Central Limit Theorem for proportionality. The statistic is inaccurate.
In probability theory, the central limit theorem establishes that, in many situations, when independent random variables are summed up, their properly normalized sum tends toward a normal distribution even if the original variables themselves are not normally distributed.
The Central Limit Theorem establishes that for a proportion p in a sample of size n:
The expected value is μ=р
The standard error is s=[tex]\sqrt{\frac{p(1-p)}{n} }[/tex]
In this problem, the expected value is different of the expected of μ=р , hence, the statistic is biased, and the correct option is E.
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