The Ubiquity of Statistical Fractal Observations

Authors

  • Roberto N. Padua
  • Randy K. Salazar University of San Jose-Recoletos

DOI:

https://doi.org/10.32871/rmrj1301.01.11

Keywords:

fractal, self – similar, statistical data

Abstract

The natural world is recognized to be fractal: from the growth of a leaf to how the trees propagate to form a forest, the neural networks, the DNA and the galaxies in space. The patterns and geometry that nature creates seem familiar and predetermined; actually it is random and unpredictable. It is this characteristic that made fractals a convenient method for such studies. Insights into the unpredictability could be a key in understanding the natural random events, like earthquakes, typhoons and other more subtle, natural occurrence like growths and cell developments. Data in different studies have always been thought of as normally distributed; however, recent investigations found that most of these statistical data are non-normal, and in a lot of cases are found to be fractal. According to Padua et al 2013, statistical fractal observations are random observations that possess stochastically self-similar patterns at various scale. In this light, this paper aims to illustrate the pervasiveness of statistical fractal observations in real-life by examining old data sets that used to be modeled in the framework of normal distribution theory. Samples of such observations will be presented in this paper.

Author Biographies

Roberto N. Padua

Dr. Roberto Natividad Padua, scientist, received his PhD in Mathematical Statistics from Clemson University, South Carolina, USA under the Fullbright-Hays scholarship grant. He is an accomplished author, a multi-awarded researcher and an internationally acclaimed lectured. Dr. Padua is a former Commissioner of CHED and currently a consultant to several State and Private Universities, conducting lectures on research and Fractal Statistics. Dr. Padua is a Summa cum Laude, BS in Mathematics Teaching graduate from the Philippine Normal College under the National Science Development Board (NSDB) program. He obtained his MS in Mathematics Education Degree from the Centro Escolar University as a Presidential Scholar.

Randy K. Salazar, University of San Jose-Recoletos

Randy K. Salazar, Mechanical Engineer, Assistant Professor of the University of San Jose Recoletos teaching Mechanical Engineering. Holder of a Masters in Science in Management Engineering from the University of San Jose Recoletos and finishing his Masters degree in Mechanical Engineering – Dynamic Design Systems at the University of San Carlos.

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Published

2013-06-18

How to Cite

Padua, R. N., & Salazar, R. K. (2013). The Ubiquity of Statistical Fractal Observations. Recoletos Multidisciplinary Research Journal, 1(1). https://doi.org/10.32871/rmrj1301.01.11

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