Statistics and Quantitative Aptitude
What this domain tests
Statistics and Quantitative Aptitude tests summarising data, measuring dispersion, basic probability, correlation and data interpretation. Expect tables, charts, averages, ratios and probability questions that require choosing the right measure rather than blind calculation.
Core rules
- Mean is affected by extreme values; median is robust to outliers; mode is the most frequent value.
- Range = maximum - minimum. Variance is the average squared deviation; standard deviation is its square root.
- For a population, divide squared deviations by N; for a sample, use n - 1 for an unbiased variance estimate.
- Probability lies between 0 and 1. For mutually exclusive events, add probabilities; for independent events, multiply probabilities.
- Correlation measures linear association, not causation. Regression estimates the dependence of one variable on another.
- In data interpretation, check units, denominators and whether the question asks for absolute change or percentage change.
Worked example
For observations 4, 6, 8, 10 and 12, mean = 40/5 = 8. Deviations are -4, -2, 0, 2 and 4; squared deviations are 16, 4, 0, 4 and 16, totalling 40. Population variance = 40/5 = 8 and standard deviation = square root of 8 = 2.83 approximately. The median is 8, so this symmetric set has mean equal to median.
Traps that cost marks
Do not use the sample denominator for a population question. Do not treat correlation as proof of causation. Do not average percentages without weighting. Do not ignore skewed data when choosing the mean. In DI, verify whether values are in thousands or lakhs.