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Expected Value, Standard Deviation, and Variance Christian, Harrison, Michael R Expected Value Definition: - “The value one would expect to find if one performed the experiment ∞ times” Formula: - E(x) = ∫Ixf(x)dx Variance & Standard Deviation Variance: The variance ( var(x) ) of a random variable X on interval I roughly measures the “deviation” (how far each f(x) is away from E(x) ) Var(x) is given by the equation: ● var(x)=∫I[x-E(x)]2f(x)dx Variance and Standard Deviation (Cont.) ● The standard deviation is given by: ○ σ = √(var(x) If: ● ● ● σ = 0 then all outcomes are identical σ = a small number, the points are clustered closely around the mean σ = a large number, the points are farther from the mean Normal Distribution - Most phenomena have probability distributions that are normal! Mean = µ Normal Distribution Continued… To find what percentage lies within a certain range, we first find our z-score with this equation: Finally, if we’re trying to find the percentage of responses that lie in between two z-score, we simply subtract the smaller from the bigger... Then, we use this chart to find the percentage of responses that lie under each z-score.