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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 (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.
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]
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.
For example, assume that the standard cost of direct labor per unit of product A is 2.5 hours x $14 = $35. Assume further that during the month of March the company recorded 4500 hours of direct labor time. The actual cost of this labor time was $64,800, or an average of $14.40 per hour. The company produced 2000 units of product A during the ...
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.
When the statistical model has several parameters, however, the mean of the parameter-estimator is a vector and its variance is a matrix. The inverse matrix of the variance-matrix is called the "information matrix". Because the variance of the estimator of a parameter vector is a matrix, the problem of "minimizing the variance" is complicated.
A simple example of such a problem is to find the curve of shortest length connecting two points. If there are no constraints, the solution is a straight line between the points. However, if the curve is constrained to lie on a surface in space, then the solution is less obvious, and possibly many solutions may exist.