In statistics, relative position refers to how the value of a data point compares to the rest of the distribution. Instead of looking only at the raw value, we use measures such as percentiles, quartiles, deciles, and z-scores to determine where a value stands relative to others. For example, if a student’s test score is at the 75th percentile, it means they performed better than 75% of the students in the group. Similarly, a z-score shows how many standard deviations a value is above or below the mean. These measures of relative position are useful for comparing values across different datasets, identifying outliers, and interpreting results in context.
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