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Hello! I am one of UConn MAGIC’s interns for the Fall 2015 Semester.
As a way of establishing the basics of Tableau, I developed – and now present to you some information about Connecticut’s standardized test score results. I encourage you to have a look and draw your own conclusions.
[xyz-ihs snippet=”Benjamin2-SATs”]
[xyz-ihs snippet=”Benjamin1-cmt-scores”]
The information represented was drawn from the U.S. Census Bureau’s 2014 1-Year American Community Survey on Grandparents. Each value represents a percentage of an age group who composes each category. This data may be useful in the observation of grandparent demographic information for Connecticut.
[xyz-ihs snippet=”grandparent-info”]
The data represented was drawn from the American Community Survey 2009-2013 5-year estimates tables for Employment Status by Age. The measured values represent a percentage of the total population within a given age group in the labor force, the percentage of the total population within a given age group that are employed, and the percentage of the total population within a given age who that are unemployed. Ages 16-54 saw decreases in employment rates between 2010 and 2013. Ages 55 and over saw increases in employment rates between 2010 and 2013.
[xyz-ihs snippet=”Employment-rate-by-age”]
The data used for this visualization was acquired from the U.S. Census Bureau’s 2014 American Community Survey 1-Year Estimates on Comparative Demographic Estimates. The measured values represent the percentage of the total population comprised of each given age group from 2010 to 2014. The total population has seen small fluctuations in size between 2010 and 2014. While age group 5-years and below have experienced decreases between 2010 and 2014, age groups 55-years and older have seen increases in total population composition between 2010 and 2014.
[xyz-ihs snippet=”Population-age-distribution”]
The Massachusetts State Data Center at the UMass Donahue Institute is hosting free in-person data training from the U.S. Census Bureau on September 21, 2015 in Hadley, MA. This event will feature two sections, a morning session focused on the 2012 Economic Census and the OnTheMap data tool for emergency management and the afternoon session will focus on how to use Census data to spur economic development. Participants may attend the morning, afternoon or both but please register using the Evenbrite links below. Seating is limited to 35 attendees per session and the sessions are filling up fast.
Session descriptions
Economic Census and Programs Session – Morning
The morning session (9am-12pm) will start with a general overview of the 2012 Economic Census and Census economic programs in general. Then there will be a demonstration of Census’s OnTheMap data tool for emergency management. Your local Census Bureau partner from the New York City regional office will close this session with an overview of the regional office’s activities and other training opportunities they offer.
Register for the Sept 21, 2015 Hadley, MA morning session here: https://www.eventbrite.com/e/us-census-bureau-training-hadley-ma-morning-session-tickets-18444290369
Census Data to Spur Economic Development Session – Afternoon
The afternoon session (1pm-4:30pm) will begin with Census teaching us how to use Census data to spur economic development. Then Census will show us how to access Longitudinal – Employer Household Dynamics data (LED data), an important new set of data we have been eagerly anticipating. Your local Census partner will close this session with a demonstration of the Census Reporter web application and an overview of the regional office’s activities and other training opportunities they offer.
Register for the Sept 21, 2015 Hadley, MA afternoon session here: https://www.eventbrite.com/e/us-census-bureau-training-hadley-ma-afternoon-session-tickets-18512106208
Location: UMass Donahue Institute 100 Venture Way #9, Hadley, MA 01035
This visualization, created for a presentation at the Connecticut Association of Boards of Education‘s Annual Summer Leadership Conference on July 27 includes data from the Connecticut State Data Center’s Population Projections for school districts in Connecticut, along with demographic, socioeconomic, and enrollment data from the U.S. Census Bureau’s American Community Survey and the CT Department of Education CEDAR data portal. This dashboard was created by Steve Batt, Zachary Guarino and Qiwei Zheng.
[xyz-ihs snippet=”Demographic-change-in-Connecticut-school-districts”]
This visualization uses data from the U.S. Census Bureau’s 2013 Annual Survey of Public Pensions State-Administered Defined Benefit Pensions Systems downloaded from American FactFinder. The thematic map indicates the ratio of pension obligations to each state’s total cash and investment holdings in its state-run public pension system at the close of fiscal year 2013. Bar graphs indicate FY13 pension fund net investment earnings, and overall pension fund investments by category (i.e. stocks, Treasury bonds, etc). Locally administered (e.g. municipal) public pension data is excluded from the graphs.
[xyz-ihs snippet=”Annual-Survey-of-Public-Pensions”]
States have remarkably diverse approaches to taxes; the U.S. Census Bureau’s Annual Survey of State Government Tax Collections collects data on revenue derived from five tax categories for 2014: Income taxes, Property taxes, License taxes, Sales and gross receipts taxes, and Other taxes. This visualization compares the relevant importance of each of these categories in contributing to the tax base of each state.
[xyz-ihs snippet=”State-government-tax-base-2014″]
The Connecticut Data Collaborative and the Connecticut State Data Center are hosting the Unlocking the Potential of Public Data workshop. The workshop will include engaging sessions, training, and discussions on public data in Connecticut and will be held on June 25, 2015.
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[xyz-ihs snippet=”Distressed-Tracts”]
This visualization uses data from the American Community Survey to display distressed census tracts, which is a tract at 60% or less of the state median household income level. This study ranges from the year 2010 to 2013.
by: Zachary Guarino