Confidence Levels

For each of the estimates given in the tables, a 95-percent confidence range can be determined with the estimate at the mid-point. To calculate the 95-percent confidence range for a given figure:

1. Multiply the RSE row factor by the RSE column factor to determine the approximate RSE.

2. Multiply the approximate RSE (divided by 100) by the estimate given in the table to determine the approximate standard error.

3. Multiply the result by 1.96 to determine approximate 2 standard errors.

4. Subtract the result of Step 3 from the given estimate to determine the bottom of the range.

5. Add the result of Step 3 to the given estimate to determine the top of the range.

The result of these steps will yield a range with the property that, in repeated surveys, the estimate would fall in the range constructed in this way 95 percent of the time.

For example, to determine the confidence range for the estimated 10.2 million midwestern housing units located in the suburbs in 1993:

1. Multiply 4.2 (the RSE row factor) by 0.9 (the RSE column factor), which yields 3.78 percent (the approximate RSE).

2. Multiply .0378 (the approximate RSE) by 10.2 million households (the estimate), which yields 0.4 million housing units (the approximate standard error).

3. Multiply 0.4 million housing units by 1.96, which yields 0.8 million housing units (approximate 2 standard errors).

4. To determine the bottom of the range, subtract 0.8 million housing units from 10.2 million housing units, which yields 9.4 million housing units.

To determine the top of the range, add 0.8 million housing units to 10.2 million housing units, which yields 11.0 million housing units.

It can then be said with 95-percent confidence that, in 1993, between 9.4 million and 11.0 million of the midwestern housing units were located in the suburbs. For each of the estimates......