Method of moments (statistics)

Related lectures (30)

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Covers risk in investment decisions, valuation of uncertain cash flows, rate of return, portfolio returns, and mean-variance utility.

Covers L-moment estimation, probability-weighted moments, and maximum likelihood inference basics.

Explains the importance of moments in measuring distribution properties, such as expectation and variance.

Explores the Large Deviations Principle, focusing on exponential tail decay and Laplace transform analysis.

Covers random variables, probability density functions, Gaussian distribution, and correlation in statistics.

Covers characteristic functions, their properties, inversion formula, and factorization property in probability theory.

Explores the transformation of random variables, joint moments, covariance, and variance.

Covers moments computation and probability distribution transformations.

Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.

Covers the normal distribution, including its properties and calculations.