Cornerstones in Quantitative Empirical Methods - Volume I: Foundations provides a complete, self-contained path from first principles to modern statistical inference, giving a comprehensive technical foundation for understanding and analyzing data problems using quantitative methods. The first part of the book provides a thorough introduction to probability theory and statistics with a focus on techniques and concepts, which are particularly useful for empirical analyses. Building directly on the first part, the second part of the book provides an introduction to estimation theory, hypothesis testing, likelihood theory, and Bayesian methods.
The nineteen concise chapters follow a transparent pattern: motivation and intuition, carefully chosen examples, main results stated as formal theorems, and a curated set of exercises that reinforce both computation and reasoning. Short illustrative datasets keep the exposition concrete while maintaining the book’s primary focus on theory. Three appendices consolidate the required background in set theory, real analysis, and simulation techniques, making the volume fully self-contained.
Designed for graduate and advanced-undergraduate courses in e.g. economics, political science, business analytics, or data science―or for motivated self-study―Volume I equips readers with the concepts and techniques needed for quantitative empirical analysis. It also prepares readers for Volume II, which builds the foundation for modelling, prediction, and causal inference in empirical studies.
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Mikkel Bennedsen, PhD, is Associate Professor at the Department of Economics and Business Economics, Aarhus University. He has received several teaching honors, including the university’s Best Lecturer award (2024). His research spans theoretical and applied econometrics, stochastic processes, and energy economics.
Allan H. Würtz, PhD, is Associate Professor and Head of the Econometrics and Business Analytics section at the Department of Economics and Business Economics, Aarhus University. An award-winning instructor, he is the author of the introductory text An Insight into Statistics and has published on econometric methodology.
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