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Probability Theory (i): One Random Variable

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Abstract

The DNA in an organism consists of very long sequences from an alphabet of four letters (nucleotides), a,g, c, and t (for adenine, guanine, cytosine, and thymine, respectively).1 These sequences undergo change within any population over the course of many generations, as random mutations arise and become fixed in the population. Therefore, two rather different sequences may well derive from a common ancestor. Suppose we have two small DNA sequences such as those in (1.1) below, perhaps from two different species, where the arrows indicate paired nucleotides that are the same in both sequences.

Keywords

  • Exponential Distribution
  • Binomial Distribution
  • Geometric Distribution
  • Discrete Random Variable
  • Continuous Random Variable

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2001 Springer Science+Business Media New York

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Ewens, W.J., Grant, G.R. (2001). Probability Theory (i): One Random Variable. In: Statistical Methods in Bioinformatics. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3247-4_1

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  • DOI: https://doi.org/10.1007/978-1-4757-3247-4_1

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4757-3249-8

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