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  1. Random variables | Statistics and probability - Khan Academy

    Random variables can be any outcomes from some chance process, like how many heads will occur in a series of 20 flips of a coin. We calculate probabilities of random variables and calculate expected …

  2. Random variables and probability distributions | Khan Academy

    A random variable is some outcome from a chance process, like how many heads will occur in a series of 20 flips, or how many seconds it took someone to read this sentence. Calculate probabilities and …

  3. Random variables (video) | Khan Academy

    Random variables are really ways to map outcomes of random processes to numbers. So if you have a random process, like you're flipping a coin or you're rolling dice or you are measuring the rain that …

  4. Random variables (video) | Khan Academy

    Random variables are really ways to map outcomes of random processes to numbers. So if you have a random process, like you're flipping a coin or you're rolling dice or you are measuring the rain that …

  5. Discrete and continuous random variables - Khan Academy

    For example, the outcome of rolling a die is a discrete random variable, as it can only land on one of six possible numbers. Continuous random variables, on the other hand, can take on any value in a given …

  6. Mean and standard deviation of a discrete random variable

    Practice calculating and interpreting the mean and standard deviation of a discrete random variable.

  7. Binomial probability (basic) (article) | Khan Academy

    She wants to find the probability that she makes exactly 2 of the 3 free-throws.

  8. Random Variables and Probability Distributions | Khan Academy

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  9. Binomial variables (video) | Khan Academy

    And what I'm going to do is I'm going to define a random variable X as being equal to the number of heads after after ten flips of my coin. Now, what makes this a binomial variable?

  10. Mean (expected value) of a discrete random variable

    We can calculate the mean (or expected value) of a discrete random variable as the weighted average of all the outcomes of that random variable based on their probabilities.