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This book begins with foundational statistical methods, including ordinary least squares (OLS) and generalized linear models (GLM). A comprehensive discussion on these two topics is undertaken in the first two chapters that explain all aspects of theory, while drawing on relevant examples and coding exercises, to illustrate concepts related with model calibration, hypothesis testing, and predicting. A firm grasp of the concepts covered in the first two chapters is also critical for understanding the concepts discussed in subsequent chapters.

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  • 发表日期：

    2025年

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  • Samit Ahlawat

摘要

This book begins with foundational statistical methods, including ordinary least squares (OLS) and generalized linear models (GLM). A comprehensive discussion on these two topics is undertaken in the first two chapters that explain all aspects of theory, while drawing on relevant examples and coding exercises, to illustrate concepts related with model calibration, hypothesis testing, and predicting. A firm grasp of the concepts covered in the first two chapters is also critical for understanding the concepts discussed in subsequent chapters.