Statistics Calculator
Enter a data set to compute mean, median, mode, range, standard deviation, and more.
σ = √(Σ(xᵢ-μ)²/n)Tips & Notes
- ✓Use sample standard deviation (n-1) when your data is a subset of the population.
- ✓Comparing mean and median reveals skewness.
- ✓Standard deviation is in the same units as the data; variance is in squared units.
- ✓A data set can have no mode, one mode, or multiple modes.
Common Mistakes
- ✗Using population formulas when sample formulas are needed (or vice versa).
- ✗Forgetting that variance is in squared units.
- ✗Assuming the mode is always unique — data can be multimodal.
- ✗Including non-numeric values in the data set.
Statistics Calculator Overview
What This Calculator Does
The Statistics Calculator accepts a comma-separated data set and computes a comprehensive suite of descriptive statistics: count, sum, mean, median, mode, range, minimum, maximum, variance (population and sample), and standard deviation (population and sample).
Measures of Central Tendency
The mean is the arithmetic average — the sum divided by the count. The median is the middle value when data is sorted. The mode is the most frequently occurring value. Each captures a different aspect of the data's center, and comparing them reveals distribution shape.
When mean ≈ median, the data is roughly symmetric. When mean > median, the data is right-skewed (pulled by high outliers). When mean < median, the data is left-skewed. The mode identifies the most common value, which may differ significantly from both mean and median in multimodal distributions.
Measures of Spread
Range is the simplest spread measure: max - min. Variance is the average squared deviation from the mean. Standard deviation is the square root of variance, expressed in the same units as the data. The distinction between population (divide by n) and sample (divide by n-1) statistics matters: use population when your data IS the entire population, sample when it represents a subset.
Applications
Every field that works with data uses descriptive statistics. Business tracks KPIs with averages and standard deviations. Medical research summarizes patient outcomes. Manufacturing monitors quality using process statistics. Education analyzes test scores. Sports evaluates player performance.