ACS Education by Veteran Status Variables - Boundaries

Retirement Notice: This item is in mature support as of February 2026 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. This layer shows education level for adults (25+) by veteran status. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of veteran civilians age 25+ who have a bachelor's degree or higher as their highest education level. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top left. Vintage: 2019-2023 ACS Table(s): B21003 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024 National Figures: data.census.gov The United States Census Bureau's American Community Survey (ACS): About the Survey Geography & ACS Technical Documentation News & Updates This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online and its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases. Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey. Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate. Either no sample observations 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 interval or upper interval of an open-ended distribution. The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate. The estimate is controlled. A statistical test for sampling variability is not appropriate. The data for this geographic area cannot be displayed because the number of sample cases is too small.

Retirement Notice: 本产品自2026年2月起进入成熟支持阶段，并将于2027年12月正式退役。目前已有该产品的新版本可供使用，Esri建议您更新地图与应用以适配新版本。

This layer shows education level for adults (25+) by veteran status. 本图层展示按退伍军人身份划分的25岁及以上成年人教育水平，数据基于普查区（tract）、县及州边界进行呈现。

This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. 本服务每年更新一次，纳入最新发布的美国社区调查（American Community Survey, ACS）5年周期数据，包含估算值与误差边际。此外还包含与该主题相关的额外计算属性，可用于制图或分析。

There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. （承接上文）

This layer is symbolized to show the percent of veteran civilians age 25+ who have a bachelor's degree or higher as their highest education level. 本图层的符号化设置用于展示25岁及以上退伍平民中，以学士学位及以上为最高教育水平的人群占比。

To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top left. 如需查看本服务中可用属性的完整列表，请前往"Data"选项卡，并选择左上角的「字段」。

Vintage: 2019-2023 ACS Table(s): B21003 数据年份：2019-2023年 ACS 表号：B21003

Data downloaded from: Census Bureau's API for American Community Survey 数据下载来源：美国人口普查局美国社区调查（ACS）API

Date of API call: December 12, 2024 API调用时间：2024年12月12日

National Figures: data.census.gov 全国数据来源：data.census.gov

The United States Census Bureau's American Community Survey (ACS): About the Survey Geography & ACS Technical Documentation News & Updates 美国人口普查局美国社区调查（ACS）：调查介绍、地理信息与ACS技术文档、新闻与更新

This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online and its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. 本即用型图层可在ArcGIS Pro、ArcGIS Online及其可配置应用、仪表板、Story Maps、自定义应用与移动应用中使用。

Data can also be exported for offline workflows. 数据也可导出用于离线工作流。

For more information about ACS layers, visit the FAQ. 如需了解更多关于ACS图层的信息，请访问常见问题解答（FAQ）。

Please cite the Census and ACS when using this data. 使用本数据时，请引用美国人口普查局与ACS。

Data Note from the Census: Data are based on a sample and are subject to sampling variability. 美国人口普查局的数据说明：本数据基于抽样调查，存在抽样变异性。

The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. 由抽样变异性导致的估算值不确定性通过误差边际来体现。

The value shown here is the 90 percent margin of error. 此处显示的为90%置信水平的误差边际。

The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. 其含义为：估算值减去误差边际与估算值加上误差边际（即置信下限与上限）所构成的区间，有90%的概率包含真实数值。

In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). 除抽样变异性外，ACS估算值还存在非抽样误差（关于非抽样变异性的讨论，请参见《数据的准确性》）。

The effect of nonsampling error is not represented in these tables. 本表格未体现非抽样误差的影响。

Data Processing Notes: 本图层会在每年最新周期的ACS数据发布时自动更新，通常为12月。本图层始终包含最新可用的ACS 5年周期估算值，会在美国人口普查局发布数据后的数日内完成年度更新。点击此处了解更多关于ACS数据发布的信息。

Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). 本图层的边界数据源自美国人口普查局TIGER地理数据库（TIGER geodatabases），具体为国家次州地理数据库（命名格式为tlgdb_(year)_a_us_substategeo.gdb）。

Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. 边界数据会与数据同步每年更新，且边界年份与美国人口普查局指定的数据年份完全匹配。

These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. 为满足制图与绘图需求，本图层已移除普查边界中的水体与海岸线。

For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. 对于普查区，水体裁剪源自TIGER提供的2020年区域水文边界子集。

Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. 面积大于等于5000万平方米的水体与河流（中大型水体）以及其他重要地物已从普查区边界中移除。

For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. 对于州与县边界，水体与海岸线源自2023年500k分辨率TIGER制图边界形状文件的海岸线数据。

These are erased to more accurately portray the coastlines and Great Lakes. 已进行移除处理以更精准地呈现海岸线与五大湖区域。

The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). 数据表格中仍保留原始的AWATER与ALAND字段（单位：平方米）。

The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico 州图层共包含52条记录，涵盖美国所有州、华盛顿哥伦比亚特区与波多黎各。

Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). 本数据服务中已移除位于海洋等水域区域且无人口的普查区（普查区代码以99开头）。

Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey. 百分比与派生计数及其关联的误差边际均为计算所得值（字段名称中带有"_calc_"前缀），并遵循美国社区调查的相关规范。

Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. 字段别名名称基于美国社区调查汇总文件文档页面中的表壳（Table Shells）文件创建。

Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. 除-5555…已被设置为0外，其他负值（例如-4444…）均已被设置为空值。

These negative values exist in the raw API data to indicate the following situations: 原始API数据中的这些负值用于表示以下情况：
1. The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate. 误差边际列显示无抽样观测值或抽样观测值过少，无法计算标准误差及误差边际，不适宜进行统计检验。
2. Either no sample observations 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 interval or upper interval of an open-ended distribution. 无抽样观测值或抽样观测值过少，无法计算估算值；或无法计算中位数之比，因为其中一个或两个中位数估算值落在开放式分布的最低区间或最高区间。
3. The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. 中位数落在开放式分布的最低区间或最高区间。
4. A statistical test is not appropriate. 不适宜进行统计检验。
5. The estimate is controlled. 估算值为受控值。
6. A statistical test for sampling variability is not appropriate. 不适宜进行抽样变异性的统计检验。
7. The data for this geographic area cannot be displayed because the number of sample cases is too small. 因抽样案例数量过少，无法显示该地理区域的数据。