Population universe or “totality of items or things”
Sample portion of the universe that has been selected for analysis
Statistical Inference The process of using sample statistics to draw conclusions about true population
Normal Distribution mean, median, mode same; 68.26% betweem +1 1 s.d. from mean; Not discrete
Power of a test NOT to make Type 1 Error
Standardized Form, normal distribution has a mean of zero and a s.d. of one
Central Limit Theorem is important in stats b/c for a large n, it says that the sampling distribution of the sample
mean is approximately normal, regardless of the shape of the population.
The s.d. of the sampling distribution of x is also known as the standard error of the mean.
P(BA) = P(AB) * P(B) / P(A)
P(AB) = P(BA) * P(A) / (B)
E(x) = ∑xP(x)
variance=
ơ
2
= ∑(xE(x))
2
P(x)
Standard Dev =
ơ
1/2
E(x) = Return
= risk
ơ
Covariance
ơ
xy
= ∑(xE(x))(yE(y))P(xy)
negative Covariance is ok
ơ
2
x+y =
ơ
x
2
+
ơ
y
2
+2 xy
ơ
Portfolio Expected Return = E(p) = wE(x) + (1w)(E(y))
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 Spring '08
 Milne
 Normal Distribution, #, 1ft, 1w, Trials Poisson Distribution, Normal Distribution mean

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