Abstract
In Mathematica Experiment 2.5.1 we observed that the cumulative d.f. and histograms of large samples drawn with finer and finer resolution or, in other words, with smaller and smaller bin size, often seem to smooth out and assume a form that is almost begging to be compressed into a single analytic formula. These various idealized limit relative frequency d.f.s, called probability density functions, and the related cumulative probability distribution functions, will be studied in this chapter. We will also learn how to simulate data sets with an a priori given probability density function.
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Bibliographical notes
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Denker, M., Woyczyński, W.A., Ycart, B. (1998). Analytic Representation of Random Experimental Data. In: Introductory Statistics and Random Phenomena. Statistics for Industry and Technology. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-2028-2_3
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DOI: https://doi.org/10.1007/978-1-4612-2028-2_3
Publisher Name: Birkhäuser, Boston, MA
Print ISBN: 978-1-4612-7388-2
Online ISBN: 978-1-4612-2028-2
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