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  2. Sales variance - Wikipedia

    en.wikipedia.org/wiki/Sales_variance

    There are two reasons actual sales can vary from planned sales: either the volume sold varied from the expected quantity, known as sales volume variance, or the price point at which units were sold differed from the expected price points, known as sales price variance. Both scenarios could also simultaneously contribute to the variance.

  3. Profit model - Wikipedia

    en.wikipedia.org/wiki/Profit_model

    The model form with 'q' and 'x' in place of' g 0 and g 1 allows profits to be calculated when only the sales and production figures are known. A spreadsheet could be prepared for a company with increasing then decreasing levels of sales and constant production. It could have another column showing profit under increasing sales and constant ...

  4. Variance (accounting) - Wikipedia

    en.wikipedia.org/wiki/Variance_(accounting)

    Variance analysis can be carried out for both costs and revenues. Variance analysis is usually associated with explaining the difference (or variance) between actual costs and the standard costs allowed for the good output. For example, the difference in materials costs can be divided into a materials price variance and a materials usage variance.

  5. Variance function - Wikipedia

    en.wikipedia.org/wiki/Variance_function

    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.

  6. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    Algorithms for calculating variance play a major role in computational statistics.A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instability as well as to arithmetic overflow when dealing with large values.

  7. Statistical dispersion - Wikipedia

    en.wikipedia.org/wiki/Statistical_dispersion

    In statistics, dispersion (also called variability, scatter, or spread) is the extent to which a distribution is stretched or squeezed. [1] Common examples of measures of statistical dispersion are the variance, standard deviation, and interquartile range. For instance, when the variance of data in a set is large, the data is widely scattered.

  8. Qualitative variation - Wikipedia

    en.wikipedia.org/wiki/Qualitative_variation

    A i is the number of data type A at sample site i, B i is the number of data type B at sample site i, K is the number of sites sampled and || is the absolute value. This index is probably better known as the index of dissimilarity (D). [44] It is closely related to the Gini index. This index is biased as its expectation under a uniform ...

  9. Explained variation - Wikipedia

    en.wikipedia.org/wiki/Explained_variation

    In statistics, explained variation measures the proportion to which a mathematical model accounts for the variation of a given data set.Often, variation is quantified as variance; then, the more specific term explained variance can be used.

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