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Central Tendencyhard
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Given a dataset where the mean is μ\muμ and the variance is σ2\sigma^2σ2, consider the effect of a nonlinear transformation y=x2y = x^2y=x2. If the original dataset is X={−2,−1,0,1,2}X = \{-2, -1, 0, 1, 2\}X={−2,−1,0,1,2}, how does the mean of the transformed set Y={xi2}Y = \{x_i^2\}Y={xi2​} compare to the square of the original mean μ2\mu^2μ2?