If both mean and variance of 50 observations $x_1, x_2, \ldots, x_{50}$ are equal to 16 and 256 respectively, then mean of $(x_1-5)^2, (x_2-5)^2, \ldots, (x_{50}-5)^2$ is
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Remember the formulas for mean ($\bar{x} = \frac{\sum x_i}{n}$) and variance ($\sigma^2 = \frac{\sum x_i^2}{n} - (\bar{x})^2$). When calculating the mean of a transformed series, expand the terms algebraically and use the sums of the original series.