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Lec . 08 – Discrete (and Continuous) Probability Distributions

Lec . 08 – Discrete (and Continuous) Probability Distributions. Independence. Discrete Uniform Distribution. What are some examples of this?. Binomial Distribution.

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Lec . 08 – Discrete (and Continuous) Probability Distributions

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  1. Lec. 08 – Discrete (and Continuous) Probability Distributions

  2. Independence

  3. Discrete Uniform Distribution What are some examples of this?

  4. Binomial Distribution If interested in obtaining the probability of r successes out of n trials over a range of r, when the probability is known – see our first example of the course!

  5. A Poisson experiment is a statistical experiment that has the following properties: The experiment results in outcomes that can be classified as successes or failures. The average number of successes (μ) that occurs in a specified region is known. Probability that a success will occur is proportional to the size of the region. Probability that a success will occur in an extremely small region is virtually zero. Poisson Distribution

  6. First, code up the Poisson distribution for a mean of your choosing, and display the histogram. Write a MATLAB code to answer the following questions about floods: Poisson Distribution Example

  7. Binomial = Distribution of the number of successes in a fixed number of trials Negative Binomial = Distribution of the minimum number of trials required to produce a fixed number of successes (e.g. number of wells drilled to find 3 exploitable reservoirs) Geometric distribution – simplest form – defines prob. distrib. of trials needed to obtain the 1st success: Pr(X=x)=(1-p)x-1p Prob. of number of trials required to obtain exactly r successes: Negative Binomial Distribution

  8. Continuous Random Variables = p.d.f.’s Poisson Distribution (discrete)  Exponential Distribution (continuous)

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