Statistical Significance Between Two Statistics

The difference between any two estimates given in the detailed tables may or may not be statistically significant. Statistical significance for the difference between two independent variables is computed as:

where S is the standard error, x₁ is the first estimate, and x₂ is the second estimate. The result of this computation is to be multiplied by 1.96, and if this result is less than the difference between the two estimates, the difference is statistically significant.

For example, in 1993, 10.2 million of the midwestern housing units were located in the suburbs, while 6.4 million midwestern households were located in the central city, for an estimated difference of 3.8 million housing units. The standard error for the 10.2 million suburban housing units estimate (x₁) is 0.39, and the standard error for the 6.4 million central city housing units estimate (x₂) is 0.31:

Multiplying .50 by 1.96 yields 1.0 million housing units. Since 1.0 housing units is less than the 3.8 million housing units difference between the 1993 midwestern suburban and central city estimates, the difference is statistically significant.