Statistics Calculator
Descriptive statistics summarize and describe the key features of a dataset: central tendency (mean, median, mode), spread (range, variance, standard deviation), and shape (skewness, kurtosis). They condense large datasets into interpretable summaries.
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Tip: For skewed data (like incomes, house prices), the median is a better measure of central tendency than the mean. Use mean when data is approximately normally distributed.
- 1Mean: sum of all values / count
- 2Median: middle value when sorted (average of two middle values if even count)
- 3Standard deviation: √(average squared deviation from mean)
- 4Quartiles: Q1 (25th percentile), Q2 (median, 50th), Q3 (75th)
Dataset: 2, 4, 4, 6, 8, 8, 10=Mean=6, Median=6, Mode=4&8, StdDev≈2.58
| Statistic | Formula | What it measures |
|---|---|---|
| Mean | Σx / n | Average value |
| Median | Middle value | Central value (robust to outliers) |
| Mode | Most frequent value | Most common value |
| Range | Max − Min | Total spread |
| Variance | Σ(x−mean)² / n | Average squared deviation |
| Std Dev | √Variance | Typical deviation from mean |
| IQR | Q3 − Q1 | Spread of middle 50% |
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Fun Fact
Average salary statistics are often misleading because mean income is higher than median income due to a small number of very high earners. The median better represents "typical" income — in the US, median household income is about $75k while mean is $100k+.
References
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