10 to 19 Employees - T421_004 - Number of Employees: Religious, Grantmaking, Civic, Professional, and Similar Organizations - Sectors by NAICS (SE) - Survey County Business Patterns 2018

Variables used in the formula:
ORG:CBP2018_006_EMPREP_230_813	Total for All Sectors: Religious, Grantmaking, Civic, Professional, and Similar Organizations

Relevant Documentation:

Excerpt from:	Social Explorer; U.S. Census Bureau; County Business Patterns 2018: Technical Documentation.
	County Business Patterns 2018: Technical Documentation -> Additional Glossary Information -> Number of establishments

Number of establishments

An establishment is a single physical location at which business is conducted or services or industrial operations are performed. It is not necessarily identical with a company or enterprise, which may consist of one or more establishments. When two or more activities are carried on at a single location under a single ownership, all activities generally are grouped together as a single establishment. The entire establishment is classified on the basis of its major activity and all data are included in that classification.

Establishment-size designations are determined by paid employment in the mid-March pay period. The size group "1 to 4" includes establishments that did not report any paid employees in the mid-March pay period but paid wages to at least one employee at some time during the year.

Establishment counts represent the number of locations with paid employees any time during the year. This series excludes governmental establishments except for wholesale liquor establishments (NAICS 4248), retail liquor stores (NAICS 44531), Federally-chartered savings institutions (NAICS 522120), Federally-chartered credit unions (NAICS 522130), and hospitals (NAICS 622).

Excerpt from:	Social Explorer; U.S. Census Bureau; County Business Patterns 2018: Technical Documentation.
	County Business Patterns 2018: Technical Documentation -> Additional Glossary Information -> Paid employees for pay period including March 12 (number)

Paid employees for pay period including March 12 (number)

Paid employees consist of full and part-time employees, including salaried officers and executives of corporations, who were on the payroll in the pay period including March 12. Included are employees on paid sick leave, holidays, and vacations; not included are proprietors or partners of unincorporated businesses.

Excerpt from:	Social Explorer; U.S. Census Bureau; County Business Patterns 2018: Technical Documentation.
	County Business Patterns 2018: Technical Documentation -> Additional Glossary Information -> First-quarter payroll ($1,000)

First-quarter payroll ($1,000)

Represents payroll paid to persons employed at any time during the quarter January to March. Data is shown in thousands of dollars ($1,000).

Excerpt from:	Social Explorer; U.S. Census Bureau; County Business Patterns 2018: Technical Documentation.
	County Business Patterns 2018: Technical Documentation -> Additional Glossary Information -> Annual payroll ($1,000)

Annual payroll ($1,000)

Total annual payroll is shown in thousands of dollars ($1,000).

Excerpt from:	Social Explorer; U.S. Census Bureau; County Business Patterns 2018: Technical Documentation.
	County Business Patterns 2018: Technical Documentation -> Additional Glossary Information -> Noise range for number of paid employees for pay period including March 12

Noise range for number of paid employees for pay period including March 12

Indicates the cell value was changed using the Noise Infusion method of disclosure avoidance. For more information on this disclosure avoidance method, see http://www.census.gov/econ/cbp/methodology.htm#disclosure

Excerpt from:	Social Explorer; U.S. Census Bureau; County Business Patterns 2018: Technical Documentation.
	County Business Patterns 2018: Technical Documentation -> Methodology -> Data Withheld from Publication

Data Withheld from Publication

In accordance with U.S. Code, Title 13, Section 9, no data are published that would disclose the operations of an individual employer.

Noise Infusion

County Business Patterns continues to apply the Noise Infusion method of data protection that began in 2007. Noise infusion is a method of disclosure avoidance in which values for each establishment are perturbed prior to table creation by applying a random noise multiplier to the magnitude data (i.e., characteristics such as first-quarter payroll, annual payroll, and number of employees) for each company. Disclosure protection is accomplished in a manner that results in a relatively small change in the vast majority of cell values. Each published cell value has an associated noise flag, indicating the relative amount of distortion in the cell value resulting from the perturbation of the data for the contributors to the cell. The flag for ' low noise (G) indicates the cell value was changed by less than 2 percent with the application of noise, and the flag for ' moderate noise (H) indicates the value was changed by 2 percent or more but less than 5 percent. Cells that have been changed by 5 percent or more are suppressed from the published tables. Additionally, other cells in the table may be suppressed for additional protection from disclosure or because the quality of the data does not meet publication standards. Though some of these suppressed cells may be derived by subtraction, the results are not official and may differ substantially from the true estimate.

The number of establishments in a particular tabulation cell is not considered a disclosure; therefore, this information may be released without the addition of protective noise. For an introduction to the noise confidentiality protection method, see Using Noise for Disclosure Limitation of Establishment Tabular Data [PDF] by Timothy Evans, Laura Zayatz, and John Slanta in the Journal of Official Statistics (1998).

Noise infusion was first applied to CBP data in 2007. Prior to 2007, data were protected using the complementary cell suppression method.

Using Noise for Disclosure Limitation of Establishment Tabular Data