![]() ![]() The larger the variance, the more spread out the data points are. It tells us how far the data points are from their average value. Variance is a measure of dispersion or spread of the data. The variance has several important interpretations, such as: Measure of Dispersion Variance = (sum of squared data points – (sum of data points)^2 / n) / (n – 1) Interpretation of Variance Variance = (sum of squared differences from the mean) / (number of data points – 1) Calculate the average of the squared differences.For each data point, subtract the mean and square the result.To calculate the variance, follow these steps: A low variance indicates that the data points are clustered closely around the mean, while a high variance indicates that the data points are widely spread out from the mean. It measures the degree of variability or spread of the data. Variance is defined as the average of the squared differences of each data point from the mean of the data set. This article will explore the meaning of variance, how it is calculated, and its various uses. It is an important concept in statistics and probability theory, widely used in fields such as finance, physics, and engineering. ![]() Variance is a statistical measure that describes how much a set of data points deviates from its mean or average value. ![]()
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