
Variance - Wikipedia
In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation is obtained as the square root of the …
Variance | Brilliant Math & Science Wiki
Variance is a statistic that is used to measure deviation in a probability distribution. Deviation is the tendency of outcomes to differ from the expected value.
VARIANCE Definition & Meaning - Merriam-Webster
The meaning of VARIANCE is the fact, quality, or state of being variable or variant : difference, variation. How to use variance in a sentence. Synonym Discussion of Variance.
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 …
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: 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? Definition, Formula, and Example
Jun 17, 2025 · What Is Variance? Variance is a statistical measurement of how large of a spread there is within a data set.
Variance: Definition, Step by Step Examples - Statistics How To
It helps us determine how far each number in the set is from the mean or average, and from every other number in the set. It is calculated by taking the average of the squared differences from …
Variance | statistics | Britannica
Dec 3, 2025 · standard deviation, in statistics, a measure of the variability (dispersion or spread) of any set of numerical values about their arithmetic mean (average; denoted by μ).
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.