U.S. Census Bureau QuickFacts: Frisco city, Texas (2024)

Value Notes

    Methodology differences may exist between data sources, and so estimates from different sources are not comparable.

    Some estimates presented here come from sample data, and thus have sampling errors that may render some apparent differences between geographies statistically indistinguishable. Click the Quick Info icon to the left of each row in TABLE view to learn about sampling error.

    The vintage year (e.g., V2023) refers to the final year of the series (2020 thru 2023). Different vintage years of estimates are not comparable.

    In Vintage 2022, as a result of the formal request from the state, Connecticut transitioned from eight counties to nine planning regions. For more details, please see the Vintage 2022 release notes available here: Release Notes.

    Users should exercise caution when comparing 2018-2022 ACS 5-year estimates to other ACS estimates. For more information, please visit the 2022 5-year ACS Comparison Guidance page.

    Fact Notes

    • (a)Includes persons reporting only one race
    • (c)Economic Census - Puerto Rico data are not comparable to U.S. Economic Census data
    • (b)Hispanics may be of any race, so also are included in applicable race categories

    Value Flags

    • -Either no or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest or upper interval of an open ended distribution.
    • FFewer than 25 firms
    • DSuppressed to avoid disclosure of confidential information
    • NData for this geographic area cannot be displayed because the number of sample cases is too small.
    • FNFootnote on this item in place of data
    • XNot applicable
    • SSuppressed; does not meet publication standards
    • NANot available
    • ZValue greater than zero but less than half unit of measure shown

    QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

    As an expert in data analysis and statistical methodologies, I bring a wealth of experience and knowledge to the table. Over the years, I have delved deep into various datasets, deciphering complex patterns, and drawing meaningful insights. My expertise extends to understanding the nuances of data sources, recognizing the impact of methodology differences, and navigating through the challenges posed by sampling errors. This proficiency has been honed through practical applications and a thorough understanding of statistical principles.

    Now, let's break down the information provided in the article:

    1. Methodology Differences:

      • The article emphasizes the presence of methodology differences among data sources, cautioning that estimates from different sources may not be comparable. This underscores the importance of understanding and acknowledging variations in the methodologies employed by different organizations or agencies when interpreting the data.
    2. Sampling Errors:

      • The article mentions that some estimates are based on sample data, and sampling errors may exist. This is a crucial aspect of statistical analysis, highlighting the potential for variations between the sample data and the entire population, rendering some apparent differences between geographies statistically indistinguishable. Users are encouraged to explore sampling error details by clicking on the Quick Info icon next to each row in the TABLE view.
    3. Vintage Year:

      • The term "vintage year" is introduced, indicating that it refers to the final year of a series (e.g., V2023). The article clarifies that different vintage years of estimates are not comparable, providing an additional layer of complexity when interpreting temporal data.
    4. Geographical Changes:

      • In Vintage 2022, Connecticut underwent a change in its planning regions, transitioning from eight counties to nine. This illustrates the dynamic nature of geographic boundaries and the need to consider such changes when analyzing data over time.
    5. Caution in Comparisons:

      • Users are advised to exercise caution when comparing ACS 5-year estimates from 2018-2022 with other ACS estimates. A link is provided for more information on the 2022 5-year ACS Comparison Guidance page, emphasizing the importance of understanding the context and potential limitations in making comparisons.
    6. Fact Notes:

      • Fact notes include information such as the inclusion of persons reporting only one race, the non-comparability of Economic Census data for Puerto Rico with U.S. Economic Census data, and the inclusion of Hispanics in applicable race categories. These notes provide additional context and considerations for accurate interpretation.
    7. Value Flags:

      • The article introduces value flags, indicating situations where no or too few sample observations were available, or where a ratio of medians cannot be calculated due to certain estimates falling in the lowest or upper interval of an open-ended distribution. These flags serve as indicators of data reliability and potential limitations.
    8. Data Display Limitations:

      • Certain geographic areas may have data suppressed or not displayed due to a small number of sample cases, emphasizing the importance of considering data availability and reliability at the local level.
    9. Data Sources for QuickFacts:

      • The article concludes by listing the various data sources for QuickFacts, including Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, and others. This information provides transparency about the diverse datasets used to compile QuickFacts data.

    In summary, my expertise allows me to navigate through the complexities of data interpretation, taking into account methodological variations, sampling errors, and the dynamic nature of geographic data. This comprehensive understanding enables me to extract meaningful insights and communicate the nuances inherent in datasets, fostering a more informed and accurate analysis.

    U.S. Census Bureau QuickFacts: Frisco city, Texas (2024)
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