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American Time Use Survey (ATS) Data Dictionary: 2010 Well-being Module Data Variables collected in the ATS Well-being Module March 2013 The ATS Well-being Module is sponsored by the National Institute
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Start by obtaining the 2010 ATUS Data Dictionary document.
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Understand the purpose and significance of the ATUS data and how it is collected.
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Identify the variables and categories that are included in the 2010 ATUS data dictionary.
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Who needs 2010 ATUS Data Dictionary?

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Researchers and analysts who are studying time use patterns and related factors.
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Government agencies and policymakers interested in understanding how individuals allocate their time.
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Social scientists and academics conducting research on various aspects of daily activities.
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Program evaluators and statisticians working on projects related to time use and productivity.
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The ATUS data dictionary public is a database or document that provides detailed information about the variables and data fields in the American Time Use Survey (ATUS). It specifies the names, descriptions, and types of the variables used in the survey.
The Bureau of Labor Statistics (BLS) is responsible for creating and maintaining the ATUS data dictionary public. It is a public resource that is available to anyone who wishes to access and understand the data collected through the ATUS.
The ATUS data dictionary public is not filled out by individuals or organizations. It is created and updated by the BLS using their expertise and knowledge of the ATUS survey design and data collection methods.
The purpose of the ATUS data dictionary public is to provide a comprehensive and standardized guide to the variables and data fields used in the ATUS survey. It helps users of the data understand the structure, meaning, and format of the variables, which aids in data analysis and interpretation.
The ATUS data dictionary public includes information about each variable used in the ATUS survey. This typically includes the variable name, description, data type, and any specific codes or categories associated with the variable. It may also provide additional information on variable construction, editing rules, and data quality.
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