1. Primers
  2. Probabilty distributions–Essential concepts
  • (Just enough) Julia for scientific informatics, modeling, and reasoning
  • Introduction
  • Basic frameworks and mechanisms
    • Orientation
    • Basics of setting up and running Julia
    • Basics of visualizing mathematical models
    • Basics of working with randomness and probabilities
    • Basics of working with data tables
  • Basics of specialized workflows
    • Basics of paleobiological fossil collection analyses
    • Basics of agent-based modeling: spatial epidemic dynamics with Agents.jl
      • Basics of agent-based modeling: spatial epidemic dynamics with Agents.jl
    • Basics of species distribution modeling
  • Primers
    • Bernoulli trial
    • Pathogen fitness as a function of virulence (Frank, 1996)
    • Virulence-transmission trade-off (Frank, 1996)
    • Julia – Environments – Global vs project
    • Julia: Functions, methods, and signatures
    • Markov property
    • Probabilty distributions–Essential concepts
    • Pseudo-random number generators
    • Pseudo-random number generators: best practices
    • Pseudo-random number generators: continuous values from discrete machines
  1. Primers
  2. Probabilty distributions–Essential concepts

Probabilty distributions–Essential concepts

Author

Jeet Sukumaran

(a) A uniform distribution assigns equal probability to every outcome.
(b)
(c)

A probability distribution is a probability measure (assignment of probability) on the set of all possible values of a random variable.

Different probability distributions may assign different probabilities to the same outcome.”

Figure 1: The same class or type distributions may also assign different probabilities to the same outcome, based on its parameter values.”
  1. The Main Ideas behind Probability Distributions - YouTube

  2. Give Me 1 Hour, I’ll Make Probability Click Forever - YouTube

  3. STARMAST - Introduction to probability

  4. Random Variables and Probability Distributions - YouTube

  5. Khan Academy - Introduction to random variables and probability distributions

  6. STARMAST - PMFs, PDFs, and CDFs

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Markov property
Pseudo-random number generators
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