More great data sets seem to be added to the U.S. Census Bureau’s  American FactFinder data engine all the time. This visualization uses data from the 2013 Annual Survey of School System Finances: Per pupil amounts for current spending of public elementary-secondary school systems by state , allowing comparison of expenditures on  instruction and support services among states.

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This is a draft Tableau dashboard displaying various Google Analytics usage metrics f for the Archives & Special Collections digital repository at the Thomas J. Dodd Research Center:  http://archives.lib.uconn.edu

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According to the the latest American Community Survey data, the period from 2007 to 2014 saw a statistically significant increase in income inequality – represented by the Gini index – in 32 states. The Gini Index represents the concentration of income in a given state or country, in a range from 0 to 1. A higher Gini index indicates greater inequality – where income is concentrated among a relatively few individuals or households; a lower Gini score represents more even income distribution.

The ACS 1-Year reports the Gini index for households in table B19083 as the middle point of a 90% confidence interval, along with a corresponding margin of error. The visualization below calculates significant change in Gini index scores from 2007-2014 – shifts outside the margin of error. In 32 states, the lower end of the range of the 2014 Gini estimate was greater than the upper range of the 2009 Gini Index estimate. In the remaining states, there was no statistically significant change from 2009 to 2014: in these cases, taking into account the margin of error, the estimates from 2009 overlapped with those from 2014.

Gini index is a commonly used economic measure, reported by organizations such as the World Bank and CIA, in its World Factbook.

[xyz-ihs snippet=”GINI-increase-by-state”]

The following post and data visualization is by guest bloggers Daniel Chiang and James Froehlich, highlighting their project for Prof. Harmon’s Economics service learning class).
This project conducted a survey of the modes of transportation access used by commuters (students, staff and faculty) to the Uconn Stamford Campus in Fall 2015. The survey was conducted during the last 3 weeks of the Fall semester.  Of the 290 Survey Respondents, 213 are undergraduates, which represents 15% of the total Uconn Stamford undergraduate enrollment in Fall 2015.

Our preliminary analysis is focused on the undergraduate students.  We found that 50% of the undergraduate respondents drive to campus.  The drivers primarily use I-95 (46%), 15% use the Merrit, 43% commute via local roads. For 38% the average trip length is 25+ miles one-way.

Across all modes of transportation, for 44% the average length of time for a one-way trip to campus is 40 to 60 minutes, and for 16% the commute time is more than 1 hour.   52% of the undergraduate respondents average four trips to campus per week, and 22% average 5 trips.

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(The following post and data visualization is by guest bloggers Patrick GIll, Robert Roig III, and Ryan WIlliams , highlighting their project for Prof. Harmon’s Economics service learning class).

This visualization depicts the prices for permit parking amongst rail station parking lots in Southwestern Connecticut. The data includes rail stations from Greenwich, CT to Greens Farms (Westport), CT. It includes monthly permitted lots as well as those that have annual permits. This visualization gives the ability to look at an individual parking lot’s permit price or all of the parking lots’ prices at once. In order to view an individual lot, select the lot in its respective dropdown filter and select “null” in the other dropdown filter. You also can compare all the monthly or annual lot prices by selecting all in the respective dropdown filter and selecting “null” in the other dropdown filter. The goal of this visualization was to help compare an individual lot’s permit price with that of the other lots by visually showing the lots’ prices side by side to see where a lot’s price sits with the rest of the market.

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This visualization depicts the utilization of parking at rail station parking lots and garages in Southwestern Connecticut. The data includes rail stations from Greenwich to Greens Farms (Westport). The data shows the number of empty spaces vs. total number of spaces at each parking lot. The figures are based on utilization counts (performed on different days of the week in 2015.) In order to view parking utilization at an individual lot, select the lot name in the dropdown filter. This will show you total spaces (Green) and empty spaces (Red) at that lot. If you select the “All” option in the dropdown filter, the visualization will show the total sum of all parking spaces in our data set as well as the total number of empty spaces in our data set. The goal of this visualization was to help show how many unused spaces there are at rail station lots which in turn could spark new ideas in order to maximize utilization of rail station parking.

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(The following post and data visualization is by guest blogger Emily Wilson, highlighting her project for Prof. Harmon’s Economics service learning class).

With the growing size of the aging population in Connecticut, this project highlights  the resources available for this population.  Senior Centers and nursing facilities are scattered throughout the state, with the highest concentrations in the Connecticut River valley.

Future analysis could delve deeper into to the needs of the citizens in the smaller towns, which only offer either a nursing facility or a senior center to ensure that the senior population is receiving a sufficient amount of services.  Additionally, future analysis could also include the proportion of seniors residing in each town in relation to the number and extent of services provided.

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The data used in this visualization was acquired from the U.S. Census Bureau’s 2009-2013 American Community Survey on Work Status in the Past 12 Months by Age by Employment Status for the Civilian Population 65 Years and Over. Each value represents the estimated amount of citizens in each age group who are either employed of unemployed.

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The data collected for poverty levels in Vernon, Connecticut, indicates that a majority of the population is living above a 200% of the poverty level. The remainder of the population is split similarly between a 100%-200% poverty level and below the poverty level. On average, poverty is more prevalent in single parent households than in households where both parents are present. The data was drawn from the American Community Survey 2009-2013 5-year estimates tables for Population Under 18 Years by Age and Poverty Level for Vernon. This data may be useful in future studies of community characteristics.

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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.

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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”]