Home > Commercial Buildings Home > 1995 Consumption and Expenditures > Detailed Tables

The "Detailed Tables" include 31 tables containing preliminary estimates of the amount of electricity, natural gas, fuel oil, and district heat that is consumed in commercial buildings and the expenditures for that energy. They also incude six tables containing estimates of the amount of electricity and natural gas used for nine specific end uses: space heating, cooling ventilation, water heating, lighting, cooking, refrigeration, office equipment, and other. The consumption and expenditures data are crosstabulated by numerous building characteristics. These data are from the 1995 Commercial Buildings Energy Consumption Survey (CBECS).

In the Quick-Reference Guide below, the 31 tables are by "data item"-- Click on the main category of interest. (File sizes range from 21 KB to 94 KB and the number of pages per file range from 6 to 16 pages.) To access the six energy end-use tables click here (file size = 136 kilobytes, 26 pages.)

Full Set of Tables - Commercial Buildings Energy Consumption and Expenditures 1995 (file size 576 KB, 99 pages).

Statistical Significance of Data

Standard Errors and Relative Standard Errors

The tables present estimates of number of buildings and floorspace for commercial buildings in the United States. Because the estimates are based on the sample surveyed, they are subject to sampling error. The standard error is a measure of the reliability or precision of the survey statistic. The value for the standard error can be used to construct confidence intervals and to perform hypothesis tests by standard statistical methods. Relative Standard Error (RSE) is defined as the standard error (square root of the variance) of a survey estimate, divided by the survey estimate and multiplied by 100.

An approximate RSE can be computed for each estimate in these tables via the use of row and column factors. The RSE for a given estimate is found by multiplying the RSE Row Factor (located in the last column) for the estimate by its RSE Column Factor (at the top of the column). This value is the approximate RSE, in percent. The RSE (divided by 100 and multiplied by the estimate) is the approximate standard error.

The 95-percent confidence range can be determined with the approximate RSE. To calculate the 95-percent confidence range for a given estimate:

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 in the table to determine the approximate standard error.

3. Multiply the approximate standard error by 1.96 to determine the approximate confidence error.

4. The estimate plus or minus the confidence error is the 95-percent confidence range.

For example, the estimate for the total amount of energy used in education buildings in the 1995 CBECS was 614 trillion Btu. (Table 1), the estimate's RSE row factor was 10.34, and its RSE column factor was 0.8. The approximate RSE is (10.34)x(0.8) or 8.3 percent. The approximate standard error was (8.3÷100)x(614 trillion Btu), or 51 trillion Btu. The 95-percent confidence error was (1.96)x(51 trillion Btu), or 100 trillion Btu. Therefore, with 95 percent confidence, the true amount of energy consumed in education buildings in the United States, in 1995, was 614 (+/- 100) trillion Btu, or in the range 514 to 714 trillion Btu.

File Last Modified: February 18, 1998

Contact:

Joelle Michaels

joelle.michaels@eia.doe.gov

CBECS Manager

Phone: (202) 586-8952

FAX: (202) 586-0018

alan.swenson@eia.doe.gov

Alan Swenson

Principal Author

Phone: 202-586-1129