Variance - GeeksforGeeks
Nov 4, 2025 · Variance is defined as the square of the standard deviation, i.e., taking the square of the standard deviation for any group of data gives us the variance of that data set.
Variance - Wikipedia
Variance is a measure of dispersion, meaning it is a measure of how far a set of numbers are spread out from their average value. It is the second central moment of a distribution, and the covariance of the …
Variance - Definition, Formula, Examples, Properties - Cuemath
Variance is a statistical measurement that is used to determine the spread of numbers in a data set with respect to the average value or the mean. The standard deviation squared will give us the variance.
How to Calculate Variance – mathsathome.com
The larger the variance, the more spread a set of data is. The variance is the square of the standard deviation. The units of variance are the square of the units measured in the data set. For example, if …
How to Calculate Variance | Calculator, Analysis & Examples
Jan 18, 2023 · The variance reflects the variability of your dataset by taking the average of squared deviations from the mean.
What Is Variance in Statistics? Definition, Formula, and Example
Jun 17, 2025 · Variance is a measurement of dispersion across a data set, comparing the difference between every other number in the set.
Variance - Definition, Symbol, Formula, Properties, and Examples
Jan 2, 2025 · What is variance in statistics. Learn its symbol, equation, and properties. How to find it explained with examples.
3 Ways to Calculate Variance - wikiHow
Dec 10, 2025 · What is variance? Variance is a measure of how spread out a data set is, and we calculate it by finding the average of each data point's squared difference from the mean. It's useful …
Variance: Definition, Formulas & Calculations - Statistics by Jim
Variance is a measure of variability in statistics that assesses the average squared difference between data values and the mean.
What is Variance in Statistics? Easy Step-by-Step Guide
The variance (Var) tells you how much the results deviate from the expected value. If the variance (σ 2) is large, the values scatter around the expected value.