Variancesfor

Variancesfor is a term used in statistics and data analysis to describe the process or function that computes variances across groups or categories within a dataset. While not a standard term in core statistical texts, variancesfor appears in software documentation, tutorials, and methodological discussions as a concise description of group-wise dispersion calculation.

Definition and scope: At its core, variancesfor refers to calculating the variance of a variable of interest within each subgroup defined by a grouping variable, or to obtain the variance across multiple features in a multivariate setting. Implementations are typically exposed as a function that accepts a data frame, a grouping key, and the target variable, and returns a mapping from group label to a variance value, optionally filtered for complete observations.

Inputs, outputs, and options: Common options include choosing the estimator (biased population variance vs unbiased sample variance, i.e., divisor n or n-1), handling of missing values (ignore, impute, or require complete cases), and whether the result is per-group variances or a pooled variance across groups. The output is usually a numeric vector or a dictionary-like structure with group identifiers as keys.

Relation to related concepts: Variancesfor is connected to group-by aggregations, descriptive statistics, and tests for homogeneity of variances such as ANOVA and heteroskedasticity checks. It supports exploratory data analysis and risk assessment in various domains.

Applications and examples: Typical uses include evaluating dispersion across experimental conditions, departments, or time periods, as well as estimating volatility within subpopulations in finance or manufacturing. For example, variancesfor(data, group_by='team', value='points') returns the variance of points within each team. See also variance, standard deviation, and group-by operations.