Percentiles
A percentile is about rank, not score. Being in the 90th percentile means about 90% of the data falls at or below your value — it does not mean you scored 90%. This distinction is the heart of nearly every GRE percentile question, and it is exactly how test scores like the GRE itself are reported. Percentiles connect neatly to quartiles: Q1 is the 25th percentile, the median is the 50th, and Q3 is the 75th. Two things to keep straight. First, a high percentile with a low raw score is entirely possible on a hard test where everyone scored low — percentile depends on the surrounding distribution, not on some fixed scale. Second, "the difference between the 80th and 90th percentiles" is a difference in rank position, and the corresponding gap in actual values can be large or small depending on how bunched the data is at that end. Read the words carefully: "percentile" signals a position in the ordered data.
✅ Solved examples
✏️ Practice — try these, take hints as needed
📝 Topic test — 8 questions
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Formula Reference Sheet
Spread & the empirical rule
| Standard deviation (idea) | typical distance of values from the mean |
|---|---|
| Add constant c to all values | SD unchanged (spread does not shift) |
| Multiply all values by k | SD is multiplied by |k| |
| 68-95-99.7 rule | ≈68% within 1 SD, ≈95% within 2 SD, ≈99.7% within 3 SD of the mean |
Positional measures
| Interquartile range | IQR = Q3 − Q1 |
|---|---|
| Quartiles | Q1 = median of lower half, Q3 = median of upper half |
| kth percentile | the value below which about k% of the data falls |
| Five-number summary (boxplot) | min, Q1, median, Q3, max |