Distributions*

• Uniform distribution: All events have equal probability.
• Var(X) = E(X^2) - E(x))^2
• Normal distribution takes the form?

  X~N(Mean, Variance)
• If X has mean m and variance v, then Z=(X-m)/v follows a standard normal distribution.
• In a normal distribution, 68% of values are within 1 standard deviation of the mean.
• In a normal distribution, 95% of values are within 2 standard deviations of the mean.
• In a normal distribution, 99.7% of values are within 3 standard deviation of the mean.
• Why would you use the inverse function for a normal distribution?

  To find the value of a random variable that corresponds to a specific probability.
• Sample mean standard deviation?

  Standard deviation / Root of number of samples
• For a normal approximate from a binomial distribution to be "accurate":

  n > max(16p/q , 16q/p)

  Or just over 50.