The standard deviation is preferred over the variance when describing statistical data since it is expressed in the same unit as the values in the data. We square the differences so that larger departures from the mean are punished more severely, and it also has the side effect of treating departures in both directions (positive errors and negative errors) equally. Standard deviation is calculated as the square root of the variance, while the variance itself is the average of the squared differences from the arithmetic mean. "Standard deviation" is often concatenated to SD or StDev and is denoted by the Greek letter sigma σ when referencing a population estimate based on a sample and the small Latin letter s when referencing sample standard deviation which is directly calculated. Standard deviation is a term in statistics and probability theory used to quantify the amount of dispersion in a numerical data set, that is - how far from the normal (average) are the data points of interest.
#WEIGHTED STANDARD DEVIATION CALCULATOR HOW TO#
One way to simplify the display of this information is to include this data on a dashboard. Notice that while the standard deviation and weighted standard deviation are applicable to a Customer Region in this example, the values are displayed for every Customer State row. This results in $957,689 for the standard deviation as compared to $1,141,237 for the weighted standard deviation of Northeast revenue. For example, since Connecticut’s revenue is greater than Maine’s revenue, and the weight in this example is the revenue value, Connecticut’s revenue is given more significance in the weighted standard deviation calculation. The weighted standard deviation also takes into account the weights of each revenue value. WeightedStDev(Revenue, Revenue) įor this example, the revenue values are also used as the weights given to each revenue value included in the standard deviation. The definition of the standard deviation metrics are as follows: The report contains the attributes Customer Region and Customer State, and the metrics Revenue, Standard Deviation, and Weighted Standard Deviation. The calculation is based on the revenue values for each state within a region and calculated at the region level. This calculation is based on the assumption that the list of values supplied in the metric represents a sample of the data for which you want to obtain the standard deviation. This example shows a report where the standard deviation and a weighted standard deviation of the revenue are calculated. For entire populations, see StDevP (standard deviation of a population). In this function, arguments correspond to a population sample as opposed to the entire population. N’: The number of weights that are not equal to zero. Values with a higher value for their weight are considered as more significant to a sample as compared to the other values in a sample. Weight is an attribute, fact, or metric representing a list of numbers to define the weight of each value.įactID is a parameter that forces a calculation to take place on a fact table that contains the selected fact. This is a group-value function.Īrgument is an attribute, fact, or metric representing a list of numbers.
WeightedStDev returns the weighted standard deviation of a population based on a sample. It is useful for comparing different sets of values with a similar mean.Ī weighted standard deviation allows you to apply a weight, or relative significance to each value in a set of values.
The standard deviation is an indicator of how widely values in a group differ from the mean (see StDev (standard deviation of a sample)). Standard Functions » OLAP functions » WeightedStDev (weighted standard deviation of a sample) WeightedSt Dev (weighted standard deviation of a sample)
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