Congressional District/State Legislative District Data Analytics Sessions

.. join me in the Congressional District/State Legislative District Data Analytics Sessions .. http://proximityone.com/cdsld/cdsld_vasessions.htm .. face-to-face sessions in the Washington, DC area.

Legislative Districts & Patterns of Neighborhood Economic Prosperity
Census tracts labeled with median household income in context VA House District 11 (bold blue boundary) in Fairfax County, VA. Use the GIS project to examine any state legislative district.

— click for larger view
— view created using CV XE GIS & associated GIS project.

CDSLD Sessions These sessions are focused on tools, data and analytical methods relating to Congressional Districts (115th CDs) and State Legislative Districts (2016 cycle SLDs). We focus on national and Virginia CDs and SLDs in context of the total population, voting population, the Citizen Voting Age Population characteristics and patterns with drill down to census block, block group, census tract, election precinct, city/place, ZIP code, county, metro and other geography.

Program details as PDF: http://proximityone.com/cdsld/cdsld_vasessions.pdf.

Anyone may attend. There is no fee. There is no promotional content. Sessions are presented by Warren Glimpse an expert on the topics covered. Learn more about the potentials of using these tools, data and methods. Get answers to your questions to learn more about what data are available, options to access the data, how to integrate these data with other data and insights into how you can use and the data. Attend one or many sessions. While there are core topics, new related material and updates are covered in each session. Join in as a continuing program. Develop and extend data analytics skills.

Patterns of Economic Prosperity by VA Senate District
– Virginia Upper/Senate SLDs by Median Household Income

– click graphic for better quality view; districts labeled with district code

More About Congressional Districts & State Legislative Districts
See the related section for more information:
• 115th Congressional Districts ..
.. Main .. http://proximityone.com/cd115.htm
.. demographic-economic tables http://proximityone.com/cd161dp1.htm
• State Legislative Districts Main .. http://proximityone.com/sld2016.htm
.. with demographic-economic interactive table
• Virginia State Legislative Districts .. http://proximityone.com/sld_va.htm
.. interactive table with incumbency details

CDSLD Data Analytics Web Sessions
Unable to join the face-to-face session? Join me in a Data Analytics Web 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: 2010-2016

.. while enrollment in many school districts is growing, for many it is declining — these include some of the largest districts. Declining enrollment in school districts can result in school closings that destabilize neighborhoods, cause layoffs of essential staff and concerns that the students who remain are some of the neediest and most difficult to educate. See related narrative.

Based on total population, the largest 10 school districts in 2016 (see table below), all experienced an increase in population over the period 2010-2016. Five of these districts had a decrease in school age population (ages 5-17 years). Five of these districts had a decrease in the number of related children in poverty in families ages 5-17 years.

See the related Web section that provides tools to analyze annual demographic data for each U.S. school district for the period 2010 through 2016. This post summarizes selected details. These data include Census Bureau official 2016 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. The 2016 estimates were released in November 2016; 2017 estimates become available in late 2018. ProximityOne uses these data in combination with other data to develop school district current estimates and annual projections through 2022 with related drill-down demographic-economic subject matter. Use the interactive table in the Web section to view, rank, compare demographic characteristics of districts of interest.

Largest 10 School Districts based on 2016 Population Age 5-17

Patterns of 2016 School Age Population in Poverty by School District
The graphic below shows school districts with total 2016 population of 1,000 or more by poverty incidence. Markers show the population ages 5-17 in families in poverty as a percent of population ages 5-17. Salmon markers: 40-50%. Red markers: 50% or more.

– view developed with CVGIS software and related GIS project.

School District Demographic Trends Interactive Table
Use the interactive table to view, rank, compare demographic characteristics of districts of interest.

More About K-12 Education & Children’s Demographics
See the related section on School District Demographic Trends 2010-2016:
http://proximityone.com/sdtrends.htm.

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 L