Probability: From Sample Spaces to Conditioning

Herfried Kohl

Chapter 16 in Managing SMEs in Times of Rapid Change, Uncertainty, and Disruption, 2024, pp 387-422 from Springer

Abstract: Key Topics in This Chapter: Mainly Quantitative In this chapter, we present the basic concepts of probability theory which are indispensable for quantitative risk management. A straightforward approach is chosen, avoiding more advanced concepts like measure theory. Primarily we consider the following: Randomness, experiments, sample spaces, random events, and their role in risk modelling. Sets and their algebra. The concept of probability, including the Kolmogorov axioms. The concept of random variables. Discrete and continuous random variables and their probability mass function, probability density function, and cumulative distribution function. Characteristics of random variables (expectation, variance, covariance, correlation, skewness, kurtosis). Marginal distribution functions. The concept of conditional probability, conditioning, and the laws of total expectation and variance.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:fuobcp:978-3-031-71272-2_16

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DOI: 10.1007/978-3-031-71272-2_16

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