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Abstract:
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Application of Multidimensional Time Model for Probability Cumulative Function to Experimental and Statistical investigations into Statistical Randomness and Normality of pi, sqrt(2), and other numbers has its place in Bayesian Statistical analysis and comes after short History of Hypothesis Testing for randomness and normality of different numbers first developed by Kendall and Smith, such as frequency, serial, poker, and gap tests for division between local and "true" randomness. Anderson-Darling, Kolmogorov-Smirnov tests of equidistribution and Siegel-Tukey test, along with mathematical theory underlying computational machine learning, such as the time complexity of computations, language recognition, and string matching followed by statistical reasoning from the Spatiotemporal Analisis and the Theory of Brownian Motion and Random Walk.
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