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  2. Bradford Factor - Wikipedia

    en.wikipedia.org/wiki/Bradford_Factor

    The factor was originally designed for use as part of the overall investigation and management of absenteeism. In contrast, if used as part of a very limited approach to address absence or by setting unrealistically low trigger scores it was considered short-sighted, unlikely to be successful and could lead to staff disaffection and grievances.

  3. Data reduction - Wikipedia

    en.wikipedia.org/wiki/Data_reduction

    Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications

  4. Utilization rate - Wikipedia

    en.wikipedia.org/wiki/Utilization_rate

    Looked at simply, there are two methods to calculate the utilization rate. The first method calculates the number of billable hours divided by the number of hours recorded in a particular time period.

  5. Shrinkage (statistics) - Wikipedia

    en.wikipedia.org/wiki/Shrinkage_(statistics)

    In statistics, shrinkage is the reduction in the effects of sampling variation. In regression analysis, a fitted relationship appears to perform less well on a new data set than on the data set used for fitting. [1] In particular the value of the coefficient of determination 'shrinks'.

  6. Blocking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Blocking_(statistics)

    Both groups are then asked to use their shoes for a period of time, and then measure the degree of wear of the soles. This is a workable experimental design, but purely from the point of view of statistical accuracy (ignoring any other factors), a better design would be to give each person one regular sole and one new sole, randomly assigning ...

  7. Sheppard's correction - Wikipedia

    en.wikipedia.org/wiki/Sheppard's_correction

    In statistics, Sheppard's corrections are approximate corrections to estimates of moments computed from binned data. The concept is named after William Fleetwood Sheppard . Let m k {\displaystyle m_{k}} be the measured k th moment, μ ^ k {\displaystyle {\hat {\mu }}_{k}} the corresponding corrected moment, and c {\displaystyle c} the breadth ...

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  9. Bessel's correction - Wikipedia

    en.wikipedia.org/wiki/Bessel's_correction

    In statistics, Bessel's correction is the use of n − 1 instead of n in the formula for the sample variance and sample standard deviation, [1] where n is the number of observations in a sample. This method corrects the bias in the estimation of the population variance.