sciences and psychometrics), common-method variance (CMV) is the spurious "variance that is attributable to the measurement method rather than to the constructs...

Common source bias can be categorised into two types: common method bias, also known as common method variance, and common source bias. Common method...

Variance-based sensitivity analysis (often referred to as the Sobol’ method or Sobol’ indices, after Ilya M. Sobol’) is a form of global sensitivity analysis...

used. Variance is the category of possible relationships between more complex types and their components' subtypes. A language's chosen variance determines...

random variable of interest, variance reduction techniques can be used. The main variance reduction methods are common random numbers antithetic variates...

Analysis of variance (ANOVA) is a family of statistical methods used to compare the means of two or more groups by analyzing variance. Specifically, ANOVA...

In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation...

elbow method. Most commonly, variation is quantified by variance, and the ratio used is the ratio of between-group variance to the total variance. Alternatively...

all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity...

squares method, the resulting F-tests are often called "exact" F-tests. The F-statistic was developed by Ronald Fisher in the 1920s as the variance ratio...

In statistics, the variance inflation factor (VIF) is the ratio (quotient) of the variance of a parameter estimate when fitting a full model that includes...

Algorithms for calculating variance play a major role in computational statistics. A key difficulty in the design of good algorithms for this problem is...

Combinatorial design Combinatorial meta-analysis Common-method variance Common mode failure Common cause and special cause (statistics) Comonotonicity...

Cognitive computer Cognitive robotics Collostructional analysis Common-method variance Complete-linkage clustering Computer-automated design Concept class...

provided a method to convert between any M-sample variance to any N-sample variance via the common 2-sample variance, thus making all M-sample variances comparable...

Bartlett's method (also known as the method of averaged periodograms), is used for estimating power spectra. It provides a way to reduce the variance of the...

pooled variance (also known as combined variance, composite variance, or overall variance, and written σ 2 {\displaystyle \sigma ^{2}} ) is a method for...

testing whether two normal samples with different variances have same means; Bhattacharyya distance – method used to separate mixtures of normal distributions...

underflow. The method below calculates the running sums method with reduced rounding errors. This is a "one pass" algorithm for calculating variance of n samples...

A variance swap is an over-the-counter financial derivative that allows one to speculate on or hedge risks associated with the magnitude of movement, i...

Markowitz model. In 1940, Bruno de Finetti published the mean-variance analysis method, in the context of proportional reinsurance, under a stronger assumption...

The method of least squares is a mathematical optimization technique that aims to determine the best fit function by minimizing the sum of the squares...

possibly corrected if coding schemes are not comparable. Test for common-method variance. The choice of analyses to assess the data quality during the initial...

2 {\displaystyle s^{2}} be the estimated variance, sometimes called the “sample” variance; it is the variance of the results obtained from a relatively...

assumption that the population error term has a constant variance, the estimate of that variance is given by: σ ^ ε 2 = S S R n − 2 {\displaystyle {\hat...

autoencoders. Importance sampling is a variance reduction technique that can be used in the Monte Carlo method. The idea behind importance sampling is...

matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between...

a method of synthesis of quantitative data from multiple independent studies addressing a common research question. An important part of this method involves...

The term cosmic variance is the statistical uncertainty inherent in observations of the universe at extreme distances. It has three different but closely...

formula for the sample variance and sample standard deviation, where n is the number of observations in a sample. This method corrects the bias in the...