Monthly Archives: February 2016

How to Assess the Hispanic Vote for the 2016 Elections?

.. a good place to start finding an answer to this question is to use the Hispanic citizen voting age population (CVAP) data. We take a look at using those data here. You can use these same tools and data to examine areas of interest.

This section is focused on using census tract level CVAP data. Census tracts cover the U.S. wall-to-wall with well-defined boundaries and average 4,000 population. The 73,057 census tracts offer a good granularity to examine citizen voting age population for neighborhoods and sections of cities or counties.

While the focus is on the Hispanic population, this population group is comprised of many specific origins (more about Hispanic population by specific origin). And, although this section is focused on the Hispanic population, the CVAP data are tabulated for several race/ethnicity combinations. We could apply these same tools to other race/ethnic combinations.

%Hispanic CVAP by Census Tract; Houston Area
— in context of Texas 114th Congressional District 29 (black boundary)
.. view developed with ProximityOne CV XE GIS and related GIS project.

This map shows how Texas 114th CD 29 has many census tracts that have high concentrations and percent of Hispanic CVAP (see legend at lower right in graphic). It is easy to where the Hispanic vote potential is by tract throughout the central Houston area. Develop thematic map patterns like this for any area of the U.S. Optionally link in voting districts/precincts, state legislative districts among many others. Modify appearance with different colors, interval/color assignments, labels among other settings.

CVAP data are available for several types of geographic areas (states, counties, census tracts, block groups, among others) from the annually updated American Community Survey (ACS) CVAP special tabulation.

How to Assess the Hispanic Vote for the 2016 Elections?
Identifying the census tracts having large numbers of Hispanic CVAP and high percentages, is a step one. But an important one. The next steps involve 1) determining the scope of the registered to vote Hispanic CVAP and 2) the registered to vote Hispanic CVAP turn-out on voting day or by absentee ballot.

Use the Interactive Table to Examine Hispanic CVAP
Use the interactive table in this related section to analyze patterns among census tracts where numbers and percent of Hispanic CVAP are large. Follow these steps to analyze pattern in the central Houston:

• Click ShowAll button below table (resets table).
• Click CountyFIPS button below table.
– refreshes table with only tracts in county 48201 (Harris County/Houston).
• Click Hispanic button below table at far right.
– refreshes table with same rows but now selected columns.
• Click the “CVAP Hispanic” column header twice.
– sorts in descending order; view now appears as:

Tract 48201221300 has the highest Hispanic CVAP (3,405) among all tracts in Harris County (48201). This tract is shown in the map below (see pointer; a zoom in to the map shown above). The tract is labeled with the tract code and the Hispanic CVAP population (3,405).

Examining Texas CD 114 29 CVAP Characteristics
The CV XE GIS Site Analysis tool was used to examine CVAP characteristics for the set of census tracts intersecting with Texas CD 114 29. This is a close but rough approximation as census tracts are not fully coterminous with CD boundaries. In this case there are 136 tracts intersecting with CD 29. Approximately 98% of the composite tracts area is coincident with the CD 29 area.

In the 2014 House election, the total CD 29 votes cast was less than 50,000. The incumbent won the election with 42,000 votes. Meanwhile, the total population for the 136 tract area was 708,709, the total CVAP was 332,060 and the Hispanic CVAP was 202,495 (ACS 2014 estimates). Roughly 150,000 eligible Hispanic CVAP voters did not vote. How to assess the potential impact of a further engaged Hispanic CVAP?

Analyzing Elections/Geographic Areas of Interest
Apply these same methods to any area in the U.S. to determine those census tracts having the highest Hispanic CVAP and the *potential* to have a relatively large Hispanic Vote in the 2016 Elections.

Join me in a Data Analytics Lab session to discuss more details about analyzing characteristics of the citizen voting age population. 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.

Tip of the Day: Median Rent by Metro

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. click Follow button at upper right.

.. the most recent estimate of median gross rent [for occupied housing units paying rent] for metropolitan areas (core-based statistical areas) is as of 2014. These data are based on the American Community Survey (ACS2014) 1-year estimates.

Option 1. Use the interactive table:
– go to http://proximityone.com/usstcbsa14dp4.htm
– median gross rent is item H132.
– scroll left on the table until H132 appears in the header column
– this column shows the 2014 ACS 1-year estimate for H132 for all CBSAs
    (and states)
– see usage notes below table.

Option 2. Use the API operation:
click this link to get H132 (median rent) using the API tool.
– a new page displays showing a line/row for each metro.
– median rent appears on the left, then metro name and code.
– optionally save this file and import the data into a preferred program.
– more about API tools.

Option 3. View the median rent in context of other attributes for a metro.
click a link in this table to select a metro of interest.
– when the metro profile displays, see section 5.2.

See this related section on metro rental markets.

This section is focused on median rent. Many other subject matter items will be apparent when these methods are used. Optionally adjust above details to view different subject matter for metros.

Join me in a Data Analytics Lab session to discuss more details about accessing demographic-economic data. Learn more about using these data and tools to meet specific interests.

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.

Academy Awards, Hollywood & Statistics

.. Hollywood thrives on statistics. Hollywood is more than a place, it is a central figure in the motion picture business and reflects something worldwide. Every week box office receipts are closely watched and often big news. The motion picture industry is big business and its activities and contributions are measured in many ways by Federal statistical agencies — often the only source of data on key attributes of the industry. The motion picture industry is defined by type of business/NAICS category 5121. See a partial summary of business/economic data sources for that sector. As for the demographics of “Hollywood”, the Census Bureau records a de facto history of the people that made Hollywood … through the decennial census. See corresponding Web page section.


— see about the Hollywood sign

This section ties together some of these data about Hollywood, the Academy Awards, statistics and data used to build statistical data. Among other data, here we look at decennial census respondent data, like that of Katherine Hepburn — read on to view more celebrity census respondent data. Attributes of these well known decennial census respondents (e.g., age, gender, race and related housing/household items) are merged together with other respondent data, like yours and mine, to develop summary statistics. This section draws substantially on data and information developed by the Census Bureau.

On February 28, 2016, the Academy of Motion Picture Arts and Sciences hosts the 88th Academy Awards at the Dolby Theater in Los Angeles, CA (see Los Angeles city ACS 5-year demographic-economic characteristics, ACS 1-year demographic-economic characteristics). During the televised ceremony, the Academy will award Oscar trophies in 24 categories, including Best Actor, Best Actress, Best Picture, and Best Original Score. The Oscars will be attended by residents of the Los Angeles metro area (see profile) including Los Angeles County (see about age-gender patterns) and Orange County.

About Hollywood
There is not a California city named Hollywood; West Hollywood is the closest thing. The Oscars event is held in the city of Los Angeles. The location is shown in the following graphic (red marker) in context with West Hollywood and Beverly Hills (red boundaries). This map was developed using TIGER/Line city/places shapefile.

– view developed using CV XE GIS and related GIS project/datasets.

Using data from the American Community Survey, we can view/analyze patterns of economic prosperity by ZIP code in the Beverly Hills area (red boundary).

– view developed using CV XE GIS and related GIS project/datasets.

More Subject Matter Detail: PUMAs. Develop custom estimates of actors and other occupations relevant to the motion picture industry using the American Community Survey Public Use Microdata Samples (PUMS). These individual population and housing respondent records enable you to develop estimates for areas with 100,000 population or more. Estimates may be developed for Public Use Microdata Areas (PUMAs). The area covered by West Hollywood and Beverly Hills is roughly equivalenced by PUMA 0603731. See map showing this area; PUMA 0603731 shown by blue boundary. Los Angeles County is subdivided into 69 PUMAs.

K-12 Education. The Beverly Hills city is almost coterminous with Beverly Hills Unified School District (see BHUSD ACS 5-year demographic-economic characteristics and population pyramid). West Hollywood city is a part of the Los Angeles Unified School District (see LAUSD ACS 5-year demographic-economic characteristics, ACS 1-year demographic-economic characteristics and population pyramid.

The Academy Awards & Data about Famous Celebrity Respondents
— based on data from the decennial censuses
— expand browser for best quality view of questionnaire respondent data (pdf)

The first Academy Awards ceremony was held on May 16, 1929. Fifteen Oscar trophies honored the motion picture industry’s actors, actresses, directors, and others for work in 1927-1928. In the years that followed, the addition of new categories honored actors and actresses in supporting roles (1936), visual effects (1939), costume design (1948), sound editing (1963), and animated feature (2001).

Today the Academy Awards have evolved into a much anticipated event featuring some of the world’s most beloved figures from the entertainment and fashion industries. Learn more about the ceremony and the industries it honors using data from the Census Bureau and other federal statistical agencies. Some details are summarized below.

Data Confidentiality. Following the “72 year rule”, pursuant to Public Law 95-416, census respondent data is held confidential for 72 years. Individual respondent data are released to the public by the National Archives and Records Administration (NARA) after 72 years. NARA released the 1930 census records in April 2002 and the 1940 census records on April 2, 2012. Individual respondent data show below is from the 1940 or earlier censuses.

Louis B. Mayer, of Metro-Goldwyn-Mayer (MGM), founded the Academy of Motion Picture Arts and Sciences in 1927 to mediate labor disputes and improve the movie industry’s image. The Academy’s 36 founding members included actors Douglas Fairbanks, Harold Lloyd, and Mary Pickford; directors Cecil B. DeMille and Raoul Walsh; producers Harry and Jack Warner; and writers Bess Meredyth and Carey Wilson.

In 1929—the year of the first Academy Awards ceremony—80 million tickets to hit films like Rio Rita starring Bebe Daniels, The Desert Song featuring music by Irving Berlin, and The Cocoanuts starring Groucho, Harpo, Chico, and Zeppo Marx earned $720 million. In 2015, Movie Web site Box Office Mojo reported that domestic audiences purchased 1.33 billion movie tickets for a total annual box office gross of approximately $11.1 billion.

Soon after the founding of the Academy of Motion Picture Arts and Sciences, data from the 1930 Census showed that 93,804 people listed their occupation as actor, dancer, showmen, or athlete. In 1940, the number increased to 97,361. In May 2014, the U.S. Bureau of Labor Statistics reported that 69,400 people worked as actors, 20,100 were dancers or choreographers, 58,900 were film and video editors and camera operators, 64,400 were multimedia artists and animators, and 122,600 worked as producers and directors.

The National Broadcasting Company (NBC) first televised the Academy Awards ceremony in 1953. In that year, 20.4 million American households owned a television. Since 1978, 98 percent or more of all American households reported owning at least one television.

The 1959 film Ben-Hur, starring Charlton Heston, won a single-film record 11 Academy Awards. Since then, two movies—Titanic (1997) and The Lord of the Rings: The Return of the King (2003)—have tied that record.

Walt Disney holds the men’s record for most Academy Award wins with 22. Costume designer Edith Head holds the women’s record with 8. Katherine Hepburn won the most Academy Awards for acting for her roles in Morning Glory (1933), Guess Who’s Coming to Dinner (1967), The Lion in Winter (1968), and On Golden Pond (1981). John Ford is the most awarded director, winning for The Informer (1934), The Grapes of Wrath (1939), How Green Was My Valley (1940), and The Quiet Man (1951).

For many, movies are not complete without popcorn. According to the U.S. Department of Agriculture, the census of agriculture found that 1,040 farms produced more than 785.7 million pounds of popcorn in 2012. Approximately 45 percent of the nation’s popcorn is grown in Nebraska, followed by Indiana (19 percent), Illinois (12 percent), Ohio (11 percent), South Dakota (3.5 percent), and Iowa (2.4 percent).

Hollywood Iconic Sign
Real estate developer H.J. Whitley erected the Hollywood Sign in 1923. Situated on Mount Lee in the Santa Monica Mountains, the sign—originally reading “Hollywoodland”—advertised Whitley’s housing development in the Hollywood area of Los Angeles, CA. Today, the sign is an iconic landmark symbolizing the state’s entertainment industry. The following map view shows the sign location at the pointer near top of map in context with the Oscar’s ceremony location shown by the red marker near the bottom of the map. Click graphic for larger view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Join me in a Data Analytics Lab session to discuss more details about analyzing characteristics of the Hollywood area and/or the motion picture industry. Learn more about using these data for areas and industries/businesses 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.

Health Insurance Coverage by Census Tract

.. the overall percent civilian non-institutionalized population with health insurance coverage changed from 85.2% in 2012 to 88.3% in 2014. Health insurance coverage is one measure among many others that are important in Healthcare Data Analytics. This section uses healthcare data analytics tools to view/analyze healthcare coverage by census tract and other geographies. See more about using health insurance coverage data in context with other health-related data in this related section.

Percent Civilian Non-institutionalized Population
    with Health Insurance by Census Tract


.. view developed with ProximityOne CV XE GIS and related GIS project.

Health Insurance Coverage Data & Interactive Table Access
Health insurance coverage data are one of several types of health-related data available in the 2014 ACS 5-year estimates. At the national level, the overall population with health insurance coverage changed from 85.2% in 2012 to 88.3% in 2014. The upper two intervals shown in the health insurance coverage by census tract map above are for the percent population with health insurance coverage at or above the national 85.2% level in 2012 (census tract data are only available from the 5-year estimates, the ACS 2014 5 year estimates are centric to 2012).

While health insurance coverage data are available in a range of demographic combinations, 25 health insurance coverage items (see table below) are available from the economic characteristics dataset for selected types of geography in these interactive tables:

ACS 2014 1-Year Estimates – data centric to mid-2014
U.S., State, CBSA/Metro
114th Congressional Districts

ACS 2014 5-Year Estimates – data are centric to mid-2012
Census Tracts
ZIP Code Areas
School Districts
State Legislative Districts

Join me in a Data Analytics Lab session to discuss more details about analyzing health and healthcare characteristics and patterns and use of data analytics to develop further detail related to your interests.

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.

Local Education Agencies by Type & State

.. the number and structure of school districts by state varies widely. Does this have an impact on educational outcomes and opportunities from state to state? In 1952, Texas had approximately 2,500 school districts (see in related section; today there are 1,027 school districts in Texas (see full table). School districts are now part of a more broadly structured set of Local Education Agencies (LEAs) which include state, regional and independent charter agencies offering elementary/secondary education. This section provides data on the count and type of LEAs by state for the 2014-15 school year.

Use the interactive table to view, rank, compare school districts/LEAs by state by type for the 2014-15 school year. These summary data are based on our processing of individual LEA data provided by individual state education agencies. Additional detail by LEA will be available later in 2016.

2014-15 LEAs by State
States labeled with total LEAs as of the 2014-15 school year. Click graphic for larger, more detailed view. Expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

2014-15 Independent Charter Agencies by State
States labeled with Independent Charter Agency (ICA) LEAs as of the 2014-15 school year (3,056). States with no ICAs not labeled. Red markers show locations of all ICAs. Click graphic for larger, more detailed view. Expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Additional views – click to view graphic; expand browser window for best quality view:
Houston area zoom-in showing ICAs with name as label
Houston area zoom-in showing charter schools (green markers)
– black boundary shows Houston ISD school district
– yellow label: total enrollment; white label: total free & reduced lunch fee

Kansas City area zoom-in showing ICAs with name as label
– black boundary shows Kansas City, MO school district
Kansas City area zoom-in showing charter schools (green markers)
– black boundary shows Kansas City, MO school district
– yellow label: total enrollment; white label: total free & reduced lunch fee

Related School District Data
See about related demographic-economic datasets, interactive tables & GIS resources: General Demographics .. Social Characteristics .. Economic Characteristics .. Housing Characteristics

States Ranked by Total LEAs
The following graphic shows states ranked by total LEAs using the interactive table — the 10 states having the largest number of LEAs. Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about analyzing LEA characteristics and pattern and use of data analytics to develop further detail related to your interests.

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.

Relating Addresses to Digital Road Segments

.. enter an address on a Google Maps page, or many other similar Web-based “find address” tools, and view that address on a map. View street detail easily. But a view of the digital road segment is not available. Answers to these questions are not available:
• what are the demographic-economic attributes for that location?
• what are the left and right side address ranges for that road segment?
• what are the geocodes on the left and right sides of that road segment?
• what are the end-point coordinates for the road segment?
• how does that road segment (the route) extend through the city or county?

Use methods described in this section to answer these types of questions and examine “Address to Digital Road Segment” relationships. An example is used that features an address shown as a red marker in the banner graphic at the top of this page (Kansas City, MO area). That address is also used in the interactive data access form below. Use these resources and methods for most addresses in the U.S. Tools reviewed here are available at no fee. Use related Web section for full functionality.

Viewing Address/Location in Context of Digital Roads
In the following graphic, a geocoded address (point shapefile) is shown as a red marker (see pointer) in context of roads (streets/lines shapefile). The Identify tool is used to show the profile of associated road segment (TLID=91447676) — an intersection to intersection segment of Oak St. Performing a query on the roads shapefile/layer to locate ID 91447676, the segment is displayed as yellow-highlighted. This application/view is reviewed in this section.

Finding Address Attributes
Use the form below to find attributes for an address. To get started, click the Find button with default settings. Results are returned/displayed on this same page. More in general, key in an address of interest, select the type of geography (more about this below) and click Find. Try your own addresses of interest; use this tool to meet recurring address lookups. Not clear on all the steps? Join us in a Data Analytics Lab session, get answers to questions.

Click following graphic for full functionality:

About the Data Content and Structure
When the Find button (above) is clicked, this page refreshes with returned data based on your query — the values entered/selected in the section above the Find button. The first portion of the data displayed provide a structured display of selected subject matter items (ACS 5-year estimates) for the type of geography selected (e.g. tracts) for that area in which the address is located. The scope of those items could be substantially expanded.

Following that portion of the display are the geographic attributes displayed as JSON output resulting from the geocoder processing of the address. This is the display content below the text “Summary of address sent and matched results:”.

Road Segment Attributes
See road segment attributes for this address under “Summary of address sent and matched results:” and “Address: {“. See that the road segment ID is shown by “tigerLineId”: “91447676”. This ID uniquely identifies this road segment among all of the more than 45 million road segments in the U.S. (see more detail in related section).

Viewing the Address with GIS Tools
1. Install CV XE GIS software (if already installed, skip step 1).
.. Install package — Windows 32/64
.. Start-up Readme
2. After installation, with CV XE GIS running, open a GIS project:
.. Use File>Open>Dialog and open the GIS project named c:\cvxe\1\cvxe_us2.gis. Perform these steps:
2.1. In the Legend Panel, uncheck layers $MHI x BG and Locations.
2.2. Use the Add Layer button to add the layer c:\cvxe\1\$$address1.shp.
.. address used in this application now appears as red marker
.. this single point shapefile was created using the CV XE Tools>FindAddress
2.3. In Legend Panel, check layer Jackson Cty MO roads.
.. now, all roads in the county can be viewed with marker.
.. optionally zoom-in to develop view like shown at top of this page.

.. view developed with ProximityOne CV XE GIS and related GIS project.

2.4. Use GIS Tools>FindShape tool to show all occurrences of “Oak St”
.. on the FindShape form the FULLNAME field is selected and set to “like” Oak St% .. all road segments having name like “Oak St%” are highlighted in yellow.

.. view developed with ProximityOne CV XE GIS and related GIS project.

2.5. Use GIS data table feature to show all occurrences of “Oak St” as table.
.. there are 155 road segment, shown in the next graphic with left and right-side address ranges .. optionally export for use in other applications.

Not clear on all the steps? Join us in a Data Analytics Lab session, get answers to questions.

Census Block Code
See section starting with “2010 Census Blocks”. In the default address run, the census block shows as “GEOID”: “290950066002016”: … state: 29 … county: 095 … tract: 006600 … block: 2016. Other items, such as the TIGER/Line segment ID and segment side, can also be important for some applications.

Any given address or location is contained with several types of statistical areas (e.g. census tract or block group) and political areas (e.g. city or county). We may want to know the demographic-economic characteristics of a location for any one or several of these geographies. Use the interactive tool on this page to access those data. For example, access/view the median household income of the location/address block group or the median household income the location/address city.

Join me in a Data Analytics Lab session to discuss more details about analyzing citizen voting age population and use of data analytics to develop further detail related to your interests.

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.

Congressional District Citizen Voting Age Population

.. congressional districts are very diverse in terms of the overall percent and geographic distribution of citizen voting age population. The size and distribution of the citizen voting age population are important as this population group determines election outcomes. Among the 114th Congressional Districts, the citizen voting age population (CVAP) ranged from 43.2% of the total population (CA40) to 81.2% (FL11) in 2014. Nationally, the citizen voting age population (CVAP) was 70.5% of the total population

% Citizen Voting Age Population by Congressional District

– view developed with ProximityOne CV XE GIS and related GIS project.

Use the interactive table discussed in this section to view/rank/compare/query national scope citizen and CVAP estimates by 114th Congressional District, state and the U.S.  Access the interactive table in this related Web page.

Examining patterns of the citizen voting age population … the Voting Rights Act prohibits development of voting districts that discriminate against potential voters on the basis of race and/or language minority status. To examine how voting districts comply with the Voting Rights Act requires data on the citizen voting age population (CVAP) by race/origin for many types of geographic areas. This section provides data analytics tools to examine ACS 2014 1-year CVAP estimates for 114th Congressional Districts. See related section for information CVAP demographics at the census tract level.

The CVAP data can be used to develop insights into alternative interpretations of “one person one vote.” The Supreme Court on May 26, 2015, agreed to hear a case that will answer a long-contested question about a principle of the American political system — the meaning of “one person one vote.” The court has never resolved whether that means that voting districts should have the same number of people, or the same number of eligible voters. The difference matters in places with large numbers of people who cannot vote legally, including immigrants who are here legally but are not citizens; unauthorized immigrants; children; and prisoners.

The CVAP estimates provide only one part of the required data. Voting district and other boundaries and data are also needed to be used in combination with the CVAP estimates. Using GIS tools, the CVAP estimates can be used in mapping applications, such as those reviewed in this section, in combination with voting district boundaries to reveal potential non-compliance in the structure of voting districts.

Interactive Table
Use this interactive table to view/rank/compare/query national scope citizen and CVAP estimates by 114th Congressional District, state and the U.S. These data are based on ACS 2014 1-year estimates found in Table B05003. See more information about computing CVAP and accessing/integrating related data.

The graphic shown below illustrates using the interactive table to rank California congressional districts in ascending order on percent citizen voting age population. Use the interactive table to examine congressional districts of interest.

Join me in a Data Analytics Lab session to discuss more details about analyzing citizen voting age population and use of data analytics to develop further detail related to your interests.

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.