measure of variability

measure of variability

(in descriptive statistics) a mathematical determination of how much the performance of the group as a whole deviates from the mean or median. The most frequently used measure of variability is the standard deviation.
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One of the advantages of using U-value as a measure of variability is that within experiments, it could be used to show the effects of contingent and noncontingent reinforcement on overall response variability.
standard deviation (SD): a measure of variability of continuous data which is calculated by taking the square root of the variance (squared differences form the mean).
This begs the question: Could a better measure of variability be constructed to control for such influences?
To adequately describe the distribution of data in a group, we need both the central tendency and a measure of variability (Figure 1).
Sigma is a statistical term that refers to standard deviation, which is a measure of variability or error in data.
In addition to the 31-point range in quarterly approval ratings, another measure of variability, statistical standard deviation, is 9 points for Hispanics, compared with 6 points for all U.
Standard deviation serves as a basic measure of variability.
Therefore, both coefficients of dissimilarity which were presented for quantitative variables could also be valid in the case of qualitative ones, and they are the measure of variability we propose for them.
Although a measure of the central tendency of a distribution of measurements and a corresponding measure of variability are not quite independent of each other--either mathematically or empirically (the standard deviation is, for example, most often positively related to the mean)--a measure of variability may provide useful information over and above that provided by the central measure, as demonstrated, for example, by recent research on performance as related to aging (e.
These absolute standardized residuals represent a measure of variability for each subject (difference between direct and predicted values).
With a distribution-based approach, clinical importance is evaluated by comparing the size of the effect of intervention to some measure of variability, such as the between-person variability in outcomes or the variability associated with repeated measures of the outcome.
The root mean squared deviation (RMSD) of the Eurozone countries REERs from the Eurozone-wide REER serves as the measure of variability.