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This book offers a comprehensive foundation in the mathematics essential for advanced statistical methods. It covers key topics such as matrices, linear algebra, vector geometry, calculus, and probability theory, alongside common probability distributions. The text also explores statistical estimation and inference, including both likelihood-based and Bayesian approaches. Concluding with a practical application in linear least-squares regression, it equips readers with the mathematical tools necessary for deeper statistical analysis.
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A Mathematical Primer for Social Statistics, John Fox
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- 2021
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