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In a positively skewed distribution, the tail extends to the right, pulling the mean higher than the median. This occurs because extreme high values disproportionately influence the mean compared to the median, which is less sensitive to outliers. For example, income data often exhibits positive skewness because a few individuals earn much more than the majority. Understanding skewness helps in choosing the right statistical methods for analysis, as normality assumptions might not hold. Why Other Options Are Wrong : A) Normally distributed data has the mean and median roughly equal. C) Negative skewness occurs when the tail extends to the left, causing the median to exceed the mean. D) Outliers often cause skewness; their absence suggests symmetry. E) The mode can vary and isn’t always lower than the mean in skewed data.
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