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A use variance is a variance that authorizes a land use not normally permitted by the zoning ordinance. [2] Such a variance has much in common with a special-use permit (sometimes known as a conditional use permit). Some municipalities do not offer this process, opting to handle such situations under special use permits instead.
These are known as by-right uses. Then there is an extra set of uses known as special uses. To build a use that is listed as a special use, a special-use permit (or conditional-use permit) must be obtained. An example of a special-use permit may be found in a church applying for one to construct a church building in a residential neighborhood ...
Analysers consider two types of variances: adverse variance and favourable variance. Adverse variance "exists when the difference between the budgeted and actual figure leads to a lower than expected profit". [14] Favourable variance "exists when the difference between the budgeted and actual figure leads to a higher than expected profit". [14]
Generally, zoning is a constitutional exercise of a state's police power [4] to protect public health, safety, and welfare. Therefore, spot zoning (or any zoning enactment) would be unconstitutional to the extent that it contradicts or fails to advance a legitimate public purpose, such as promotion of community welfare or protection of other properties.
Nonconforming use in urban planning the use of land that was authorised at the time the use was created but is no longer allowed due to changes made to the zoning restrictions after that time. [1]
Common and special causes are the two distinct origins of variation in a process, as defined in the statistical thinking and methods of Walter A. Shewhart and W. Edwards Deming. Briefly, "common causes", also called natural patterns , are the usual, historical, quantifiable variation in a system, while "special causes" are unusual, not ...
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
For exactness, the t-test and Z-test require normality of the sample means, and the t-test additionally requires that the sample variance follows a scaled χ 2 distribution, and that the sample mean and sample variance be statistically independent. Normality of the individual data values is not required if these conditions are met.