Abstract
The purpose of this chapter is to lure you into reading the rest of the monograph. We present four examples of probability questions that would be unpleasant to solve by hand, but are solvable with computational probability using APPL (A Probability Programming Language). We define the field of computational probability as the development of data structures and algorithms to automate the derivation of existing and new results in probability and statistics. Section 12.3, for example, contains the derivation of the distribution of a well-known test statistic that requires 99,500 carefully crafted integrations.
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References
Hogg RV, McKean JW, Craig AT (2005) Introduction to the mathematical statistics, 6th edn. Prentice-Hall, Upper Saddle River, New Jersey
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Drew, J.H., Evans, D.L., Glen, A.G., Leemis, L.M. (2017). Computational Probability. In: Computational Probability. International Series in Operations Research & Management Science, vol 246. Springer, Cham. https://doi.org/10.1007/978-3-319-43323-3_1
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DOI: https://doi.org/10.1007/978-3-319-43323-3_1
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