Get MP Zoning Variance Application 2009-2024

A variance is a request to deviate from current Zoning Bylaw requirements. If granted, a variance essentially waives a specific requirement of the Zoning Bylaw. For example, if a property owner wants to locate a structure closer to a lot line than the Zoning Bylaw allows, a variance would be required.

The term variance refers to a statistical measurement of the spread between numbers in a data set. More specifically, variance measures how far each number in the set is from the mean (average), and thus from every other number in the set.

A Variance is a request for relief from strict application of zoning regulations to alleviate an unusual hardship to a particular property. For example, a homeowner may request that a room addition be permitted to cover more of the property than the Zoning Ordinance would normally allow.

In general, a variance will only be granted if the following 4 criteria are met: Compliance with the zoning laws would cause undue hardship on the landowner; The proposed construction is necessary for reasonable use of the property; The proposed construction would not alter the essential character of the neighborhood;

A zoning variance provides a property owner with the legal permission to build structures or use land in ways that are contrary to existing local zoning conditions.

A variance is a request by a property owner to deviate from current zoning laws for any number of reasons. A zoning law, or zoning ordinance, is put in place by a local governing body to dictate how property in a particular area or zone can be utilized.

The variance is a measure of variability. It is calculated by taking the average of squared deviations from the mean. Variance tells you the degree of spread in your data set. The more spread the data, the larger the variance is in relation to the mean.

In statistics, variance measures variability from the average or mean. It is calculated by taking the differences between each number in the data set and the mean, then squaring the differences to make them positive, and finally dividing the sum of the squares by the number of values in the data set.