Foundations of Probability and Statistics

Joe Suzuki
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Joe Suzuki: Osaka University, Graduate School of Engineering Sciences

Chapter Chapter 2 in Graphical Models and Causal Discovery with Python, 2026, pp 15-38 from Springer

Abstract: Abstract In this chapter, as the groundwork for learning causal discovery with graphical models, we introduce the basic concepts of probability and statistics. We begin by defining fundamental terms such as events, probabilities, and random variables and then introduce representative probability distributions: the binomial, normal, Poisson, and Gamma distributions. We also discuss concepts used to describe relations among multiple random variables—joint distributions, independence, correlation coefficients, and covariance matrices.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-95-5308-2_2

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DOI: 10.1007/978-981-95-5308-2_2

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