Journal of Cultural Economics 20: 25–50, 1996. c 1996 Kluwer Academic Publishers. Printed in the Netherlands. 25

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• Statistical models
• Discrete choice
• Demand
• Elasticity
• Economic model
• Utility
• Marginal utility
• Random variable
• Taste
• Economics
• Consumer theory
• Microeconomics

MFE 237H: Quantitative Asset Management Notes on Minimum Variance Portfolios Professor Jason Hsu UCLA Anderson School of Management Minimum Variance Portfolio

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• Summary statistics
• Matrices
• Probability theory
• Variance
• Covariance
• Sample mean and sample covariance
• SAS
• Multivariate random variable
• Principal component analysis
• Statistics
• Covariance and correlation
• Data analysis

6.042J Chapter 17: Random variables and distributions

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• Mathematical analysis
• Probability and statistics
• Random variable
• Randomness
• Probability density function
• Probability distribution
• Expected value
• Cumulative distribution function
• Variable
• Probability theory
• Mathematics
• Statistics

09:TOPIC. Characteristic functions, cont’d. This lecture develops an inversion formula for recovering the density of a smooth random variable X from its characteristic function, and uses that formula to

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12:TOPIC The normalizing transformation and friends. This section studies some asymptotic expansions that are closely related to Edgeworth’s expansion for the cdf. Let X be a real random variable with a

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2007 Paper 8 Question 7 Information Theory and Coding (a) Suppose that X is a random variable whose entropy H(X) is 8 bits. Suppose that Y (X) is a deterministic function that takes on a different value for each value o

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1997 Paper 8 Question 11 Information Theory and Coding The input source to a noisy communication channel is a random variable X over the four symbols a, b, c, d. The output from this channel is a random variable Y over

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19:TOPIC. Cumulants. Just as the generating function M of a random variable X “generates” its moments, the logarithm of M generates a sequence of numbers called the cumulants of X. Cumulants are of int

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10:TOPIC. Moment generating functions. The nth moment of a random variable X is E(X n ) (if this quantity exists); the moment generating function (MGF) of X is the function defined by

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17:TOPIC. Densities. This section discusses densities. We begin with a review of the concept of a density of a random variable and the relation between densities and dfs. We then turn to the so-called chan

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