varianceanalyse

Varianceanalyse, or analysis of variance, is a term used to describe methods for examining differences between observed outcomes and expected values. It is applied in statistics and in managerial accounting, where it refers to different but related concepts: statistical analysis of variance (ANOVA) and variance analysis of actual versus budgeted or standard costs.

In statistics, ANOVA is a collection of models that partition the total variation in a data set into components attributable to different sources, such as factors or groups. The basic idea is to test whether the means across groups are equal or whether observed differences are likely due to random variation. Common forms include one-way ANOVA and two-way ANOVA, and more advanced variants like MANOVA or repeated measures ANOVA. The procedure computes sums of squares, degrees of freedom, mean squares, and an F-statistic, then assesses significance with a p-value. Key assumptions include independence of observations, normality of residuals, and homogeneity of variances. Interpretation focuses on whether the observed differences are unlikely under the null hypothesis and on identifying contributing factors after appropriate post hoc analyses.

In managerial accounting, variance analysis compares actual results with planned or standard costs to identify deviations. Typical variances include material price variance, material quantity variance, labor rate variance, labor efficiency variance, and overhead variances. The process involves setting standards or budgets, collecting actual data, calculating variances, and investigating root causes to inform management actions. Variances are labeled favorable or unfavorable and guide decisions on pricing, purchasing, staffing, and process improvements.

Both uses of varianceanalyse rely on careful data collection, appropriate modeling, and cautious interpretation within the broader decision-making context.