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  1. Nicole Seaman

    P1.T2.20.8. Probability matrix

    Learning objectives: Explain how a probability matrix can be used to express a probability mass function. Compute the marginal and conditional distributions of a discrete bivariate random variable. Explain how the expectation of a function is computed for a bivariate discrete random variable...
  2. Nicole Seaman

    P1.T2.20.4. Random variables (2nd of 2)

    Learning objectives: Explain the differences between a probability mass function and a probability density function. Characterize the quantile function and quantile-based estimators. Explain the effect of a linear transformation of a random variable on the mean, variance, standard deviation...
  3. Nicole Seaman

    P1.T2.20.3. Random variables (first of two)

    Learning objectives: Describe and distinguish a probability mass function from a cumulative distribution function and explain the relationship between these two. Understand and apply the concept of a mathematical expectation of a random variable. Describe the four common population moments...