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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 probability theory, the law of total variance[ 1] or variance decomposition formula or conditional variance formulas or law of iterated variances also known as Eve's law, [ 2] states that if and are random variables on the same probability space, and the variance of is finite, then. In language perhaps better known to statisticians than to ...
Conditional variance. In probability theory and statistics, a conditional variance is the variance of a random variable given the value (s) of one or more other variables. Particularly in econometrics, the conditional variance is also known as the scedastic function or skedastic function. [ 1] Conditional variances are important parts of ...
e. In statistics, the variance function is a smooth function that depicts the variance of a random quantity as a function of its mean. The variance function is a measure of heteroscedasticity and plays a large role in many settings of statistical modelling. It is a main ingredient in the generalized linear model framework and a tool used in non ...
The coefficient of variation (CV) is defined as the ratio of the standard deviation to the mean , [ 1] It shows the extent of variability in relation to the mean of the population. The coefficient of variation should be computed only for data measured on scales that have a meaningful zero ( ratio scale) and hence allow relative comparison of ...
The standard deviation of a random variable, sample, statistical population, data set, or probability distributionis the square rootof its variance. It is algebraicallysimpler, though in practice less robust, than the average absolute deviation.
Sum ← Sum + x. SumSq ← SumSq + x × x. Var = (SumSq − (Sum × Sum) / n) / (n − 1) This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to ...
Statistical test. In statistics, one-way analysis of variance(or one-way ANOVA) is a technique to compare whether two or more samples' means are significantly different (using the F distribution). This analysis of variancetechnique requires a numeric responsevariable "Y" and a single explanatory variable "X", hence "one-way".