Statistics Calculator
Paste in a dataset and get all the key stats at once: mean, median, mode, variance, and standard deviation. You can switch between sample and population standard deviation depending on what your data represents.
How to use
- Type or paste your numbers, separated by commas or spaces.
- Choose whether your data is a sample (use this for most real-world data) or the full population.
- Results show up right away - mean, median, mode, variance, and standard deviation all at once.
Related tools:
Descriptive statistics summarise a dataset with a few key numbers. The mean (average) tells you the central value, the median tells you the middle value when sorted, and the mode tells you the most frequent value. Standard deviation measures how spread out the values are from the mean. A low SD means values are clustered closely; a high SD means they are widely spread.
These measures are fundamental in data analysis, research, finance, and academics. For example, in finance, standard deviation measures investment risk (volatility). In education, mean and median marks describe class performance. Our calculator handles all common descriptive statistics for any list of numbers you provide.
Frequently Asked Questions
What is the difference between mean and median?
Mean is the sum of all values divided by the count. Median is the middle value when data is sorted. Mean is affected by outliers: a single very large value pulls it up, while median is more robust. For example, in income data, median income is more representative than mean income because a few very high earners distort the mean.
When should I use standard deviation vs variance?
Variance is the average of squared deviations from the mean. Standard deviation is the square root of variance, expressed in the same units as the original data. Standard deviation is easier to interpret (e.g. Ā±2 kg) while variance is used in mathematical formulas. For most practical purposes, use standard deviation.
What is population vs sample standard deviation?
Population SD divides by N (total count), used when you have data for the entire population. Sample SD divides by Nā1 (Bessel's correction), used when your data is a sample from a larger population. For most student and analytical purposes, sample SD is appropriate.
What does a high standard deviation mean?
A high standard deviation means the data points are spread widely from the mean. In finance, high SD = high volatility = higher risk. In test scores, high SD means students performed very differently from each other. Low SD means the data is consistent and clustered around the mean.