Abstract
Being inferential in character, Monte Carlo methods rely on statistics; but at the same time they are useful in several fields where statistical jargon is unfamiliar. Some readers may therefore find it convenient to have a brief account of those statistical techniques and terms which arise most often in Monte Carlo work. What follows in this chapter is a mere outline; fuller information appears in standard textbooks such as Cochran [1], Cramér [2], Kendall and Stuart [3], and Plackett [4]. Although Markov chains are important in Monte Carlo work, we defer a discussion of them until §9.1.
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References
W. G. Cochran (1953). Sampling techniques. New York: Wiley.
H. Cramér (1946). Mathematical methods of statistics. Princeton Univ. Press.
M. G. Kendall and A. Stuart (1961). The advanced theory of statistics, Vols I—III. London: Charles Griffin.
R. L. Plackett (1960). Principles of regression analysis. Oxford: Clarendon Press.
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© 1964 J. M. Hammersley and D. C. Handscomb
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Hammersley, J.M., Handscomb, D.C. (1964). Short Resumé of Statistical Terms. In: Monte Carlo Methods. Monographs on Applied Probability and Statistics. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-5819-7_2
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DOI: https://doi.org/10.1007/978-94-009-5819-7_2
Publisher Name: Springer, Dordrecht
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