Random Variable Mean and Variance
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Random Variable Mean and Variance
How to compute the mean and variance of discrete random variables. Sample problems illustrate each step in the computation. Includes free video lesson.
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SOLVED:The mean (μ) of a random variable is the expected value. We can use the probability model to find the standard deviation (σ) in much the same way we found the standard deviation for sample data. We calculate the square root of the expected value of squared deviations from the mean: σ=√(∑i=1^n(xi-μ)^2 ×P(xi)). (a) Suppose a carnival game offers prizes described by the probability model below. Find the expected value of the game. (b) Find the standard deviation of the value of the prizes. (
SOLVED:The mean (μ) of a random variable is the expected value. We can use the probability model to find the standard deviation (σ) in much the same way we found the standard deviation for sample data. We calculate the square root of the expected value of squared deviations from the mean: σ=√(∑i=1^n(xi-μ)^2 ×P(xi)). (a) Suppose a carnival game offers prizes described by the probability model below. Find the expected value of the game. (b) Find the standard deviation of the value of the prizes. (
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SOLVED:The mean (μ) of a random variable is the expected value. We can use the probability model to find the standard deviation (σ) in much the same way we found the standard deviation for sample data. We calculate the square root of the expected value of squared deviations from the mean: σ=√(∑i=1^n(xi-μ)^2 ×P(xi)). (a) Suppose a carnival game offers prizes described by the probability model below. Find the expected value of the game. (b) Find the standard deviation of the value of the prizes. (
SOLVED:The mean (μ) of a random variable is the expected value. We …
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