Revision as of 00:26, 28 June 2024 by Admin (Created page with "'''Solution: E''' The expected number of pennies in a single roll equals <math>\mu = 49.8 </math> and the variance equals <math>\sigma^2 = 0.36 </math>. In particular, the net loss for <math>n</math> rolls is approximately normally distributed with mean <math>0.02n</math> and variance <math>n\sigma^2</math>. Hence the probability of a net loss equals <math display = "block">P(Z \geq \frac{-0.02n}{\sigma \sqrt{n}}) = P(Z \geq \frac{-\sqrt{n}}{30})</math> where <math>Z</...")
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Exercise


ABy Admin
Jun 28'24

Answer

Solution: E

The expected number of pennies in a single roll equals [math]\mu = 49.8 [/math] and the variance equals [math]\sigma^2 = 0.36 [/math]. In particular, the net loss for [math]n[/math] rolls is approximately normally distributed with mean [math]0.02n[/math] and variance [math]n\sigma^2[/math]. Hence the probability of a net loss equals

[[math]]P(Z \geq \frac{-0.02n}{\sigma \sqrt{n}}) = P(Z \geq \frac{-\sqrt{n}}{30})[[/math]]

where [math]Z[/math] is a standard normal variable. The 1th percentile for a standard normal equals -2.326, hence we need

[[math]] \frac{\sqrt{n}}{30} \geq 2.326 \implies n \geq 4869.25 [[/math]]

00