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The sample mean ( sample average) or empirical mean ( empirical average ), and the sample covariance or empirical covariance are statistics computed from a sample of data on one or more random variables . The sample mean is the average value (or mean value) of a sample of numbers taken from a larger population of numbers, where "population ...
Deviation (statistics) Plot of standard deviation of a random distribution. In mathematics and statistics, deviation serves as a measure to quantify the disparity between an observed value of a variable and another designated value, frequently the mean of that variable. Deviations with respect to the sample mean and the population mean (or ...
When only a sample of data from a population is available, the term standard deviation of the sample or sample standard deviation can refer to either the above-mentioned quantity as applied to those data, or to a modified quantity that is an unbiased estimate of the population standard deviation (the standard deviation of the entire population).
If the statistic is the sample mean, ... experimental data are often summarized either using the mean and standard deviation of the sample data or the mean with the ...
Average absolute deviation. The average absolute deviation ( AAD) of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability. In the general form, the central point can be a mean, median, mode, or the result of any other measure of central tendency or any ...
The variance of a random variable is the expected value of the squared deviation from the mean of , : This definition encompasses random variables that are generated by processes that are discrete, continuous, neither, or mixed. The variance can also be thought of as the covariance of a random variable with itself:
In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample -based statistic. If an arbitrarily large number of samples, each involving multiple observations (data points), were separately used in order to compute one value of a statistic (such as, for example, the sample mean or ...
In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real -valued random variable about its mean. The skewness value can be positive, zero, negative, or undefined. For a unimodal distribution (a distribution with a single peak), negative skew commonly indicates that the tail is on the ...