Search results
Results from the WOW.Com Content Network
In variance analysis (accounting) direct material total variance is the difference between the actual cost of actual number of units produced and its budgeted cost in terms of material. Direct material total variance can be divided into two components: the direct material price variance, the direct material usage variance.
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.
In variance analysis, direct material usage (efficiency, quantity) variance is the difference between the standard quantity of materials that should have been used for the number of units actually produced, and the actual quantity of materials used, valued at the standard cost per unit of material.
According to the PMBOK (7th edition) by the Project Management Institute (PMI), Cost variance (CV) is a "The amount of budget deficit or surplus at a given point in time, expressed as the difference between the earned value and the actual cost." [19] Cost variance compares the estimated cost of a deliverable with the actual cost. [20]
The variance of randomly generated points within a unit square can be reduced through a stratification process. In mathematics , more specifically in the theory of Monte Carlo methods , variance reduction is a procedure used to increase the precision of the estimates obtained for a given simulation or computational effort. [ 1 ]
Price variance (Vmp) is a term used in cost accounting which denotes the difference between the expected cost of an item (standard cost) and the actual cost at the time of purchase. [1] The price of an item is often affected by the quantity of items ordered, and this is taken into consideration.
Engineering statistics involves data concerning manufacturing processes such as: component dimensions, tolerances, type of material, and fabrication process control. There are many methods used in engineering analysis and they are often displayed as histograms to give a visual of the data as opposed to being just numerical.
Let the unknown parameter of interest be , and assume we have a statistic such that the expected value of m is μ: [] =, i.e. m is an unbiased estimator for μ. Suppose we calculate another statistic such that [] = is a known value.