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Financial modelling terms explained

Standard deviation is a measure of the dispersion of a set of data from its mean. The standard deviation is used in statistics as a measure of how far data points are spread out from the mean.

Standard deviation is a measure of how dispersed a set of data is around its mean. It is computed by taking the square root of the variance, which is a measure of the average squared deviation of the data from its mean. Standard deviation is usually denoted by the symbol Ïƒ.

Standard deviation is a measure of the variability of a set of data. It is calculated by taking the square root of the variance. The variance is calculated by taking the difference of each data point and the mean, and then dividing by the number of data points.

Standard deviation is a measure of the variability of a set of data. It is important to know your standard deviation because it can help you to identify whether your data is clustered around a particular value, or whether it is more spread out. If your data is clustered around a particular value, then your standard deviation will be low. If your data is more spread out, then your standard deviation will be high. Knowing your standard deviation can help you to make informed decisions about your data.

The standard deviation is a measure of how much a set of data points varies from the mean, while the mean is the average of all the data points in a set. To calculate the standard deviation, you first calculate the mean of a set of data points, and then you calculate the square of the difference between each data point and the mean. You then add all of these squared differences together, and divide by the number of data points in the set. The mean is simply the average of all the data points in a set.

A standard deviation is a measure of the dispersion of a set of data points from their mean. It is calculated by taking the square root of the variance of the data. Standard deviation is often used to identify outliers in data sets. An example of a standard deviation can be found below.

The standard deviation for the sample data is 2.71. This means that the data points are dispersed 2.71 standard deviations from the mean. The data set has a high degree of variability.

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