
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 …
Varianza: Qué es, fórmula y ejemplos - Economipedia
May 26, 2025 · La varianza es una forma de entender cuán diferentes son los datos que estamos estudiando con respecto a un valor medio.
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.
¿Qué es la varianza en estadística? Definición, Fórmulas y Aplicaciones
Jan 24, 2025 · ¡Explore el núcleo matemático de la varianza! Aprende sus fórmulas, propiedades y aplicaciones en estadística para medir la dispersión de datos y analizar la variabilidad de manera …
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.
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.
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.
Varianza - var (X) | Estadísticas - RT
En probabilidad y estadística, la varianza de una variable aleatoria es el valor promedio de la distancia al cuadrado del valor medio.
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.