Effect of Changing a Data Point
This is the single most GRE-characteristic idea in the whole chapter, and it rewards reasoning over computation. When you add, remove or alter one value in a set, each statistic responds differently, and knowing the pattern lets you answer without recomputing anything. The mean moves in the direction of the change, by (change in total)/(number of values) — so adding a value above the current mean raises it, and below it lowers it; adding a value exactly equal to the mean leaves it unchanged. The median often does not move at all, because a new value on one side of the middle may only shift the position slightly, or not at all. The mode changes only if the frequencies change. The classic Quantitative Comparison here gives you a set, changes one value, and asks you to compare the new mean or median with the old — the answer is usually reachable by pure logic. A powerful shortcut: adding a value equal to the current mean keeps the mean fixed but can still move the median, so "the mean is unchanged" never implies "the median is unchanged".
✅ Solved examples
✏️ Practice — try these, take hints as needed
📝 Topic test — 8 questions
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Formula Reference Sheet
Measures of centre
| Arithmetic mean | mean = (sum of values) / (number of values) |
|---|---|
| Sum from the mean | sum = mean × n |
| Median (odd n) | the single middle value once sorted |
| Median (even n) | average of the two middle values once sorted |
| Mode | the value(s) that occur most often |
Spread & weighting
| Range | range = greatest value − least value |
|---|---|
| Weighted mean | (Σ weightᵢ × valueᵢ) / (Σ weightᵢ) |
| Missing value | missing = (target mean × n) − (known sum) |
| New mean after adding x | (old sum + x) / (n + 1) |