Category Archives: Houston ISD

National Children & Education Statistics Program Updates

.. NCES Program updates .. tools, data & methodology to examine national scope children & education .. school, school district & extended geographic-statistical data with drill-down to school and intersection level. See more about the NCES Program below.

New this Week
ACS 2015 school district demographic-economic interactive tables
– view, compare, analyze selected/all U.S. school districts
– more focused blog updates coming soon.

School Districts with Highest Median Household Income
Use the interactive table to examine economic characteristics of school districts. Below is a list of the 10 school districts having the highest median household income developed using the Economic Characteristics interactive table. Develop similar views for metros and states of interest.

– ranked on item E062 — median household income.
– click graphic for larger view.

Use GIS tools to develop thematic pattern maps such as the one shown below with NCES GIS projects. Select from hundreds of statistical measures. Create your own regional;/district views. Integrate other data.

Patterns of Economic Prosperity by School District
– median household income (item E062 in table)

– view developed with CVGIS software & related GIS project and data.
– click graphic for larger view.

See the School Districts Economic Characteristics Interactive Table.

About the National Children & Education Statistics Program
The National Children & Education Statistics (NCES) Program provides access to tools, data & methodology to examine national scope children’s demographics & education-related characteristics. These resources enable stakeholders to view and analyze detailed geographic and statistical data at the school, neighborhood, community, attendance zone, school district and higher level geography. Integrate these data with drill-down demographic-economic data to the census block and intersection levels. Examine characteristics of schools, school districts and education data with related and higher level geography including urban/rural, cities, counties, metros, state and the U.S.

See NCES Main Section.

Contents: Summary of NCES Program Resources
Click a link to view more detail on a selected topic.
Updates: New Resources, Events & Related Topics
Analytics, Blogs, Studies
Using Software Tools & Datasets
01 Mapping & Visual Analysis Tools
02 School District Annual Demographic-Economic Data Resources
03 Children’s Demographics & Living Environment by School District
04 School District Enrollment & Operational Characteristics
05 School District Finances: Sources & Uses of Funds
06 School District Geographic Size & Characteristics
07 School District-ZIP Code Area Relationship Table
08 K-12 Public Schools
09 K-12 Private Schools
10 K-12 Public School Attendance Zones
11 K-12 Public Schools by Urban/Rural Status
12 Census Tract Demographic-Economic Characteristics
13 Metropolitan Area Situation & Outlook Reports

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

School District Demographic Trends: 2010-2015

.. data and tools to examine how school districts of interest are changing … based on total population, the largest 10 school districts in 2015, all experienced an increase in total population over the period 2010-2015. Five of these districts had a decrease in school age population (ages 5-17 years). Four of these districts had a decrease in the number of related children in families ages 5-17 years. See characteristics of districts in this interactive table. See the related Web section for more details.

School Districts with 2015 Population 100,000 or More
More than 600 of the total 13,245 school districts have a total 2015 population of 100,000 or more (red markers).

– view developed with CVGIS software and related GIS project.

Using New 2015 Estimates Released December 2016
– for use in 2017 ESEA Title I Allocations
Analyze annual demographic data for each U.S. school district for the period 2010 through 2015. These data include the Federal official 2015 estimates available for all districts. Developed for use as inputs for the ESEA Title I allocation formula, the data have broader uses of interest to school district demographics stakeholders. Use the interactive table in this section to view, rank, compare, query demographic characteristics of districts of interest.

The annual estimates for each school district include:
• total population
• number of children ages 5 to 17
• number of related children ages 5 to 17 in families in poverty

Using Interactive Data Tools
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic measures. The following graphics illustrate how the table can be used. Click graphic for larger view.

Total Population — 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

School Age Population — 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

Related Children Ages 5-17 in Poverty
– 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

Try it yourself. Use the table to examine a set of districts on your selected criteria in for a state/area of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Largest School Districts Enrollment Characteristics

..  while school district enrollment is reported by school districts, only public school enrollment is reported. Public and private school enrollment are available by district from the American Community Survey (ACS 2015).  With few exceptions, school districts do not report on demographic-economic characteristics of the school district.  These data are only available from ACS. See the related interactive table to access and compare enrollment characteristics of school districts of interest.

In 2015, there were 1,016 school districts with total population of 65,000 or more (of total 14,650) for which “1-year estimates” were tabulated.  These estimates are based on respondent data for calendar year 2015.  This section summarizes selected enrollment characteristics of the largest districts and provides access to much more detail for each of these districts.

Largest 10 School Districts
The following graphic shows the largest 10 school districts based on the size of the 2015 school age population ages 5-to-17. Click graphic for larger view.

Mapping the Largest School Districts
The following graphic shows locations of the largest school districts as red markers. Click graphic for larger view that opens in a new window. Expand browser window for bets quality view. The larger view shows school district locations on context of metropolitan statistical areas (MSAs).

  view created using CV XE GIS software and related GIS project.

School Districts Tabulated in ACS 2015
ACS 2015 data are tabulated for 14,650 school districts (among many other wide-ranging geography). The following table shows the number of districts for which 1-year estimates and 5-year estimates are tabulated. There are 1,016 districts for which 1-year estimates were tabulated.

These data show enrollment of residents of the district whether enrolled in that district or otherwise. Enrollment data are provided for preschool, K-12 and college and not enrolled.

Using the School District Enrollment Interactive Table
The following graphic illustrates use of the interactive table (click that link to use the table) showing enrollment in kindergarten by school district ranked in descending order.

– click graphic for larger view.

Using the table, you can select total, public or private enrollment for selected grade ranges.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

New ACS 2015 1-Year Demographic-Economic Data

.. essential data to assess where we are, how things have changed and how things might change in the future down to the sub-neighborhood level. The American Community Survey (ACS) is a nationwide survey designed to provide annually updated demographic-economic data for national and sub-national geography. ACS provides a wide range of important data about people and housing for every community across the nation. The results are used by everyone from planners to retailers to homebuilders and issue stakeholders like you. ACS is a primary source of local data for most of the 40 topics it covers, such as income, education, occupation, language and housing. ProximityOne uses ACS to develop current estimates on these topics and 5-year projections. This section is focused on ACS 2015 data access, integration and use and is progressively updated.

New ACS 2015 1-year estimates are available as of September 15, 2016.

Importance of ACS: Assessing Demographic-Economic Change
Oil prices plummeted in late 2014. How has this affected people and households in areas hardest hit? Find out for wide-ranging geographies using the ACS 2015 1-year estimates. Compare to ACS 2014 1-year estimates. Use the ACS 2016 1-year estimates (September 2017) to see how the impact has continued. Demographic-economic conditions change for many reasons; oil price changes are just one.

Keep informed about ACS developments and related tools and applications:
• Updates are sent to ProximityOne User Group members (join here).
… access special extract files and GIS projects available to members.
• ACS updates and applications are covered in the Data Analytics Blog.
• ACS data access, integration & use … join us in a Data Analytics Lab session.

In the weeks ahead, the following ProximityOne information resources will be updated with new ACS 2015 1-year data:
U.S.-State-Metro Interactive Tables
• Demographic component section of Metro Situation & Outlook Reports .. example for Dallas metro
• Housing characteristics component section of Metro Situation & Outlook Reports .. example for Dallas metro
Demographic-Economic Trend Profiles
• Special study reports.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Children’s Demographics by School District

.. data and tools to analyze children’s demographics by school district ..  the ACS 2014 median household income for the Houston ISD, TX (HISD) was $46,069 (all households) compared to $41,896 (grade relevant children’s households). How does economic prosperity (or choose from many other attributes) vary between the total population of an area and to those of total children or grade relevant children by type of enrollment in districts of interest? See related Web section with interactive table.

This section summarizes data and tools to access to the children’s demographic-economic data, based on the 2014 American Community Survey (ACS 2014) school district special tabulation (SDST), for each/all school districts. These data provide insights into the population, social, economic and housing characteristics of total children and grade relevant children — in contrast to the total population and housing. Use the interactive table below to view, rank, compare, query children’s characteristics.

Patterns of Economic Prosperity by School District; Children’s Households
— Median Household Income for Grade Relevant Children Households
The following thematic map shows patterns of median household income for grade relevant children households by school district for Texas and adjacent states. Click graphic for larger view (shows metros). Expand browser to full extent for best quality view.

View developed using CV XE GIS software and associated GIS project.

Additional Views:
Dallas metro area
Houston metro area
Los Angeles metro area

Importance of these Data
The annually updated SDST data are a unique source of data to help stakeholders understand demographic-economic characteristics of total children as well as grade relevant children. The real power of these data is that they enable analysis of children’s living characteristics by type of enrollment (enrolled in public school, enrolled in private school, not enrolled) by school district. For example, in this Houston ISD, TX profile it can be determined that of those grade relevant children who ‘speak English less than “very well”.
– enrolled in public school
… 36,995 or 18.7% of total grade relevant children enrolled public
– enrolled in private school
… 810 or 3.9% of total grade relevant children enrolled private (very low)
– not enrolled
… 3,265 or 30.9% of total grade relevant children not enrolled (very high)

How does Houston ISD compare to Dallas ISD? … to Los Angeles Unified? … use these data to find out. Whether ability to speak English, or other living/demographic environmental characteristics, these are among the factors that can primarily influence educational outcomes.

Comparing the Number of Households
The total number of households compared to the number of households with grade relevant children is often in the range of 3-to-4 to 1. The following table shows illustrative examples for selected districts.

Scope of the School District Special Tabulation
The School District Special Tabulation is a tabulation of the characteristics of children who reside within the boundaries of a school district. Note that such residents/children might attend a school located outside of the school district of residence. Subject matter items are tabulated for these seven universes:
• all children — population ages 0-19, 18 & 19 not high school graduates
• all school age, grade relevant children
– children enrolled
– children enrolled in public school
– children enrolled in private school
– relevant children not enrolled
See about related data

Children’s Demographics by Type of Enrollment
  — Interactive Table
The following graphic illustrates use of the interactive table to rank districts by total relevant children and views percentage distributions by type of enrollment. Note that among the largest 10 districts, Las Vegas (Clark County, NV) has the largest percent not enrolled (12.x% — far right column). Use the full interactive table to compare contrast district based on your criteria.

– click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn

Analyzing ACS 2014 1-Year Supplemental Data

.. examining 2014 characteristics of areas with population 20,000 and over  .. this section summarizes how to use the America Community Survey (ACS2014) “supplemental” data (ACS2014S) to access more current estimates than otherwise available. The America Community Survey “supplemental” data are just that, a supplemental set of ACS 2014 1-year estimates — for areas 20,000 population and over. See the related Web section providing more detail.

The importance of the ACS 2014S data are two fold.
1 – 2014 1-year estimates for a larger number of areas than available from the ACS 2014 1-year (ACS2014) estimates.
2 – more current (2014) data for those areas only available from the 5-year estimates (centric to 2012) that are between 20,000 and 65,000 population.

The ten cities/places with the highest 2014 median family income based on 1-year estimates were all under 65,000 population. These cities were not included in the ACS 2014 1-year standard estimates but were included in the ACS 2014 1-year supplemental estimates. See list below.

This section provides an overview of the ACS 2014 supplemental data and provides a summary of tools, interactive table and GIS project, to analyze characteristics of these areas. These data are used by ProximityOne to develop/update annual county demographic-economic projections. See schedule of related 2016 updates.

Scope of Expanded Geography Available
As shown in the table below, 2014 1-year “supplemental” estimates are available for more than twice as many counties from the ACS2014S compared to the ACS2014 “standard” 1-year estimates. However, there area a more limited set of subject matter data available from the ACS2014S data compared to both the ACS 2014 1-year and 5-year estimates.

MSA/MISA: Metropolitan Statistical Areas/Micropolitan Statistical Areas Counties: county and county equivalent

ACS 2014S Data Availability by County
The following graphic shows the additional counties for which ACS 2014 1-year estimates are available using the “supplemental” data.
• ACS 2014 1-year “standard” estimate counties — blue fill pattern
• ACS 2014 1-year “supplemental” estimate counties — orange fill pattern
• Only ACS 2014 5-year estimates available for remaining counties
Click graphic for larger view; expand browser window for best quality view. The larger view shows metropolitan area (MSA) boundaries. Note that for example, ACS 2014 1 year data are available for all counties in the Austin and San Antonio metros (see pointer) — previously unavailable..

.. view developed with ProximityOne CV XE GIS and related GIS project.
.. any CV XE GIS user can create this view using the default US1.GIS project

ACS2014S Tables — scroll section
The ACS 2014 supplemental data include 42 tables and a total of 229 data items. Br> The table number and descriptions are summarized below.

View full table/item detail in tables shells: ACS 2014S Table shells (xls)

ACS 2014 Selected Supplemental Items for Selected Geography
  — interactive table
The interactive table contains all geography for which the ACS2014S data have been tabulated for these geographies: U.S., state, county, city/place, 114th Congressional District, MSA/MISA, PUMA, urban area and school district. The table provides access to key selected items.

The following graphic illustrates use of the interactive table. First cities/places were selected using the Type drop-down below the table. Next, the table is ranked in descending order on median family income. As shown in the graphic the largest 10 cities/places were under 65,000 population. Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

State and Regional Decision-Making Information

Organized on a state-by-state basis, use tools and geographic, demographic and economic data resources in these sections to facilitate planning and analysis. Updated frequently, these sections provide a unique means to access to multi-sourced data to develop insights into patterns, characteristics and trends on wide-ranging issues. Bookmark the related main Web page; keep up-to-date.

Using these Resources
Knowing “where we are” and “how things have changed” are key factors in knowing about the where, when and how of future change — and how that change might impact you. There are many sources of this knowledge. Often the required data do not knit together in an ideal manner. Key data are available for different types of geography, become available at different points in time and are often not the perfect subject matter. These sections provide access to relevant data and a means to consume the data more effectively than might otherwise be possible. Use these data, tools and resources in combination with other data to perform wide-ranging data analytics. See examples.

Select a State/Area

Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
D.C.
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming

Topics for each State — with drill-down to census block
Visual pattern analysis tools … using GIS resources
Digital Map Database
Situation & Outlook
Metropolitan Areas
Congressional Districts
Counties
Cities/Places
Census Tracts
ZIP Code Areas
K-12 Education, Schools & School Districts
Block Groups
Census Blocks

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.