Formula Sheet — Statistics
Card 1: Mean deviation
| Data type | Formula |
|---|---|
| Range | Maximum Minimum |
| Ungrouped, about (mean or median) | |
| Grouped () | |
| Grouped median |
Card 2: Variance and standard deviation
| Data type | Formula |
|---|---|
| Ungrouped | |
| Computing identity | ; |
| Frequency data | |
| Shortcut () | ; |
| First naturals | mean , variance |
| Standard deviation | , in the data's own units |
Card 3: JEE Corner
| Tool | Statement |
|---|---|
| Linear transformation | ; |
| Shift only | variance unchanged |
| Scale only | variance |
| Coefficient of variation | ; lower = more consistent |
| Combined mean | |
| Combined variance | , |
| Basic inequality | , equality only for constant data |
Last-Minute Mistake Checklist
- Deviations about the mean sum to zero — that is why mean deviation needs and variance needs squares; never average raw deviations.
- Variance vs SD: variance is in squared units, SD in original units — answer the one the question asked and say which is which.
- The median for grouped data comes from the formula ; picking the midpoint of the median class instead is a classic error.
- Gapped classes need the half-unit continuity correction before midpoints and medians (16-20 becomes 15.5-20.5).
- In the shortcut method, multiply back: , and — forgetting (or adding to ) wrecks the answer.
- Shift never changes variance; scale changes it by — and the SD takes , so a negative multiplier still gives a positive SD.
- is the entry point for missing-observation and corrected-statistics problems — recover both sums before touching anything.
- Correcting a wrong entry changes by (right wrong) and by (right wrong); omitting an entry also reduces .
- Combined mean is weighted, not the plain average of the two means — sizes matter.
- C.V. needs and is the only fair consistency comparison when means or units differ; with equal means, comparing SDs suffices.
How this chapter flows on: Probability (next chapter) closes Class 11; in Class 12, random variables re-import mean and variance as expectation and spread of distributions — with these formulas assumed fluent.