Categories of Data in the Tables:
Column Categories
Row Categories

Statistical Significance of Data

Row and Column Factors

The tables provide row factors in the far-right column and column factors on the top line of each table. These factors are to be used to determine the Relative Standard Error (RSE) for each estimate, which in turn can be used to determine the standard error and the confidence level of the estimate and to determine whether the difference between any two figures is statistically significant. However, since the RSE’s are only approximate, standard errors, confidence intervals, and statistical tests must also be regarded as only approximate. For more details about the derivation of the row and column RSE factors, see Appendix B, "Quality of the Data."

To calculate the RSE for a specific estimate, multiply the row factor by the column factor, as illustrated in Figure 3.1, an excerpt from Table 3.1a of this report. This table shows that 10.2 million housing units in the Midwest were located in suburban areas. Multiplying 4.2 (the row factor) by 0.9 (the column factor) yields an approximate RSE of 3.8 percent.

Figure 3.1. Use of RSE Row and Column Factors

Table 3.1a. Household Characteristics by Census Region and Climate Zone, Million U.S. Households, 1993

Standard Errors

Since the estimates presented in the following tables are based on a sample of residential housing units, they are subject to sampling error, or standard error. To determine the standard error for an estimate in these tables, multiply the approximate RSE by the estimate. For example, to determine the standard error of 10.2 million housing units located in the suburbs of the Midwest in 1993, multiply 10.2 million housing units by .0378 (the approximate RSE). The result, 0.39 million housing units, is the approximate standard error for the estimate.

Confidence Levels
Statistical Significance Between Two Statistics

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All Detailed Tables (file size 1,097KB) pages: 182.

Topical Sections

Household Characteristics Presents data relating to location, type, ownership, age, size, construction, and householder demographic and income characteristics. - (file size 257 kilobytes) pages: 40.

Space Heating Presents data describing the types of heating fuel and equipment used for main and secondary heating purposes. - (file size 117 kilobytes) pages:20.

Air-Conditioning Presents data describing selected household characteristics including location, number of rooms and area cooled and air-conditioning usage. - (file size 43 kilobytes) pages: 6.

Appliances Presents data describing the frequency and characteristics of energy-intensive appliances found in most households. - (file size 205 kilobytes) pages: 32.

Light Usage Presents data describing the number and usage of incandescent and fluorescent indoor lights and outdoor lights. - (file size 73 kilobytes) pages: 12.

Usage Indicators Presents data describing usage of heating and cooling equipment, including thermostat settings at various times of the day, equipment using hot water, and cooking appliances. - (file size 143 kilobytes) pages: 24.

Conservation Presents data describing conservation measures taken by the household, participation in demand-side management programs, and types of windows in the housing unit. - (file size 142 kilobytes) pages: 24.

Equipment Purchase Presents data describing the purchase and replacement of heating and cooling equipment, refrigerators, and water heaters in the past 4 years and purchase considerations such as price and energy efficiency. - (file size 142 kilobytes) pages: 24.

Within each section, except for Air-conditioning and Light Usage, four sets of tables are presented. Each set of tables is comprised of data presented in terms of counts of millions of U.S. households and in terms of percent of U.S. households. Each count table is paired with its comparable percent table so that for each topic or variable counts are presented on the left-hand page and percentages presented on the facing right-hand page. The four sets of tables are entitled:

• Census Region and Climate Zone
• Year of Construction
• Type and Ownership of Housing Unit
• Family Income.

Eileen M. O'Brien

RECS Survey Manager

Phone: (202) 586-1122

Fax: (202) 586-0018