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    Advanced Statistics for Quants

    From the axioms of probability to advanced modeling techniques, this is your complete guide.

    • Properties of the Normal Distribution and the Z-Score
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    • Linear Combinations of Independent Normal Random Variables
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    • Multivariate Normal Distribution
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    • Marginal and Conditional Distributions of Multivariate Normal
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    • Applications in Portfolio Theory and Financial Modeling
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    • The t-Distribution (Student's t)
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    • The χ² (Chi-Squared) Distribution
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    • The F-Distribution (Fisher–Snedecor)
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    • Convergence in Probability and the Weak Law of Large Numbers (WLLN)
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    • Convergence in Distribution and the Central Limit Theorem (CLT)
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    • Slutsky's Theorem and the Delta Method
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