How Much Snow Does It Take To Close Your School?

A recent post on reddit provided a map of the US, broken down by counties, which predicts the general amount of snow needed before your local school closes. It was created based on a combination of local news reports, a survey, and average snowfall levels from NOAA maps. It then makes an approximation of the differing levels of snow it takes to call off school. While the map is based on hundreds of data points, it is by no means considered to be 100% accurate. Nonetheless, it is sort of interesting to think about, given the deep South's recent "Snomageddon".

How Much Snow to Close School ?

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2012 Income and Poverty Data for Municipalities in Herkimer and Oneida Counties

With the release of the Five Year ACS Estimates in December, it is now possible to get data for every municipality in the region, regardless of size. Below are two tables (click to enlarge them) which have income and poverty data for each municipality in Herkimer and Oneida Counties. If you'd like to see other data for either county as a whole, visit the ACS matrix link.

Herkimer County Data

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Oneida County Data

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Why the ACS Asks What It Does? A Review of the Housing and Population Questions

So the American Communities Survey (ACS) is the new (if being more than 10 years old is still considered new) way of getting data about our country out there for policymakers, businesses and the general public. The ACS, which is around 60 questions long, is really the ONLY resource for many of the questions asked.


So where do these sixty plus questions come from? And why are they asked? The links below will take you to either the Housing ACS questions, or the Population ACS questions and provide you with a review of each question and some information about how the data is used and why it is required.

 Housing Questions Review

 Population Questions Review 

How We Read in America: Books, eBooks and AudioBooks Demographics

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The Pew Internet and American Life Project recently released a report about Americans and their reading habits when it comes to books, ebooks and audiobooks. Especially interesting is their breakdown of the demographics of who uses each of those three reading resources.

Overall, 76% of adults read a book in some format over the previous 12 months. The typical American adult (i.e. the median) read or listened to 5 books in the past year, and the average for all adults (i.e. the mean) was 12 books. Neither the mean nor median number of books read has changed significantly over the past few years.

As of January of 2014, 50% of Americans now have a dedicated handheld device–either a tablet computer like an iPad, or an e-reader such as a Kindle or Nook for reading e-content. That figure has grown from 43% of adults who had either of those devices in September of 2013.

The proportion of Americans who read e-books is growing, but few have completely replaced print books for electronic versions. The percentage of adults who read an e-book in the past year has risen to 28%, up from 23% at the end of 2012. At the same time, about seven in ten Americans reported reading a book in print, up four percentage points after a slight dip in 2012, and 14% of adults listened to an audiobook. Though e-books are rising in popularity, print remains the foundation of Americans’ reading habits. Most people who read e-books also read print books, and just 4% of readers are “e-book only.”

Extremely interesting is the demographic breakouts for each of these various reading trends.

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Among the cited observations and trends were that women are more likely than men to have read a book in the previous 12 months, and those with higher levels of income and education are more likely to have done so as well. In addition, blacks are more likely to have read a book than Hispanics. There were no significant differences by age group for rates of reading overall.

In terms of book format, women are more likely than men to have read a print book or an e-book, as are whites and blacks compared with Hispanics and those with higher education and incomes compared with others. Younger adults are also more likely than those ages 65 and older to have read e-books, as are those who live in urban and suburban areas compared with rural residents. Finally, adults with higher levels of education are more likely to have read audiobooks than those who did not attend college.

There is much more information included in the report so please visit the PEW website and explore the rest of their findings!

Super Bowl Census Style: The Numbers Behind the Game and Cities

Super Bowl Trends

21

Out of 47 Super Bowls, the team whose city had the smaller population won the game 21 times. In the past 14 years, the city with the smaller population has won 10 times (71.4 percent).
Source: National Football League.

1995

Year that the NFL instituted the salary cap, which was intended to allow smaller market teams to be more competitive with large market teams. The team with the larger population had won the last 13 Super Bowls prior to the salary cap, and 19 of the first 28 Super Bowls (67.9 percent) before the 1995 season.
Source: National Football League

270

How many more people lived in Seattle than Denver on July 1, 2012, making Seattle 0.04 percent larger than Denver.
Source: Census Population Estimates

Denver (Broncos)

23rd

Where Denver ranked on the list of the nation's most populous cities. The estimated population of Denver on July 1, 2012, was 634,265. Denver gained 14,980 people from July 1, 2011, to July 1, 2012. At the time of the Broncos' first season in 1960, the 1960 Census population for Denver was 493,887.
Source: Census Population Estimates and Decennial Census

44.7%

Percentage of Denver residents 25 and older who had a bachelor's degree or higher in 2012; 86.0 percent had at least graduated from high school. The respective national figures were 29.1 percent and 86.4 percent. Denver's percentage of 25 and older who at least graduated from high school is not significantly different from the national figure.
Source: 2012 American Community Survey

26.3%

Percentage of Denver residents 5 and older who spoke a language other than English at home. The national average was 21.0 percent.
Source: 2012 American Community Survey

$50,488

Median household income for Denver. The national median was $51,371. Denver's median household income is not significantly different from New York's median household income or the national figure.
Source: 2012 American Community Survey

$251,200

Median home value of owner-occupied homes in Denver. The national median was $171,900.
Source: 2012 American Community Survey

24.6 minutes

Average amount of time it took Denver residents to get to work; 68.6 percent of the city's workers drove to work alone, 8.7 percent carpooled and 7.2 percent took public transportation. Nationally, it took an average of 25.7 minutes to get to work. Denver's carpooled percentage is not significantly different from Seattle's carpooled percentage.
Source: 2012 American Community Survey

Seattle (Seahawks)

22nd

Where Seattle ranked on the list of the nation's most populous cities. The estimated population of Seattle on July 1, 2012, was 634,535. Seattle gained 12,638 people from July 1, 2011, to July 1, 2012. At the time of the Seahawks' first season in 1976, the 1970 Census population for Seattle was 530,831.
Source: Census Population Estimates and Decennial Census

57.7%

Percentage of Seattle residents 25 and older who had a bachelor's degree or higher in 2012; 93.6 percent had at least graduated from high school. The respective national figures were 29.1 percent and 86.4 percent.
Source: 2012 American Community Survey

23.9%

Percentage of Seattle residents 5 and older who spoke a language other than English at home. The national average was 21.0 percent.
Source: 2012 American Community Survey

$64,473

Median household income for Seattle. The national median was $51,371.
Source: 2012 American Community Survey

$415,800

Median home value of owner-occupied homes in Seattle. The national median was $171,900.
Source: 2012 American Community Survey

25.9 minutes

Average amount of time it took Seattle residents to get to work; 49.2 percent of the city's workers drove to work alone, 8.5 percent carpooled and 19.7 percent took public transportation. Nationally, it took an average of 25.7 minutes to get to work. Seattle's average commute time is not significantly different from the national average, and Seattle's carpooled percentage is not significantly different from Denver's carpooled percentage.
Source: 2012 American Community Survey

New York City

1st

Where New York City ranked on the list of the nation's most populous cities. The estimated population of New York City on July 1, 2012, was 8,336,697. New York City gained 67,058 people from July 1, 2011, to July 1, 2012.
Source: Census Population Estimates

34.7%

Percentage of New York City residents 25 and older who had a bachelor's degree or higher in 2012; 79.6 percent had at least graduated from high school. The respective national figures were 29.1 percent and 86.4 percent.
Source: 2012 American Community Survey

49.2%

Percentage of New York City residents 5 and older who spoke a language other than English at home. The national average was 21.0 percent.
Source: 2012 American Community Survey

$50,895

Median household income for New York City. The national median was $51,371. New York's median household income is not significantly different from Denver's median household income.
Source: 2012 American Community Survey

$478,400

Median home value of owner-occupied homes in New York City. The national median was $171,900.
Source: 2012 American Community Survey

39.3 minutes

Average amount of time it took New York City residents to get to work; 22.6 percent of the city's workers drove to work alone, 4.7 percent carpooled and 55.9 percent took public transportation. Nationally, it took an average of 25.7 minutes to get to work.
Source: 2012 American Community Survey

Social Networking and Internet Use Differences Among White, Black, and Hispanic Users

Back in August of 2013 I posted about a PEW study measuring adult use of the internet. Well recently the Wall Street Journal released a study of how Twitter is attempting to better aim it's ads based on the demographics of its users. As it turns out Twitter's user base is more racially diverse than U.S. Internet users as a whole. Blacks, Hispanics and Asian users account for 41% of Twitter's 54 million U.S. users, compared with 34% of the users of rival Facebook and 33% of all U.S. Internet users, according to Pew Research Center's Internet and American Life Project.

The graphic below allows some comparisons between the various prominent social media and their user demographics.

Weather, You Like it Or Not...

With another blast of cold frigid arctic air blanketing the area, some people might wonder if this is the coldest temperatures we've ever seen. Well that answer would be no....for now ! According to the New York State Climate Office, housed at Cornell University, minus 29 degrees (in 1995) was the coldest temperature ever recorded in Utica.

The State Climate Office has all sorts of weather related data that you can see based on city location. The page on Utica shows the historic temperatures, precipitation, and snowfall by month. Take a look at the Utica records, or any of the other major cities in New York State by visiting the Climate Office website.

And while I'm not sure about the rest of the country, all I know is that when I turned on the shower this morning, it snowed for the first 10 minutes ! THAT'S COLD !

Revisiting MOE:A Lesson About Margins of Error in the ACS for Median Household Income

A while back I posted about understanding the margins of error (MOEs) in the American Community Survey estimates. As you may recall, ALL estimates implicitly come with a margin of error - that is to say some degree to which the provided estimate may be close to the actual number for characteristic "X". Because the estimates are based on fairly small samples for the ACS, statisticians like to build in some "fudge factor" and recognize that the estimate is probably right "plus or minus some margin of error". So we all recognize that the resulting sample data is probably not dead on the actual number if we surveyed every single person. Instead we build a "confidence interval" around the sample estimate which we are willing to say (typically) we're 90% confident that the actual number, if we surveyed the entire population, would be within.

Perhaps a good example would be something like median household income.

The 2012 ACS Five Year Estimate shows that the median household income for Oneida County is $49,148. Now this is based on a sample in which about one in 50 households were surveyed. If we surveyed ALL of the other households in the county would we get the same median income number? Possibly, but very, VERY unlikely. So instead, what demographers and statisticians like to go is take the margin of error (MOE) for this piece of data and construct a 90% confidence interval around this data point. this is done by going one MOE above and one MOE below the estimated number.

In the income case, we would add and subtract the MOE (which is +/- $999) and now say that we are 90% confident that the ACTUAL value of the median household income for the county lies between  $50,147 and $48,149.

Let's take this a step further and look at this visually. Here's the Oneida County Median Household income on a graph; the green box represents the estimated value, and the vertical line shows the range of 90% confidence interval/ We are 90% confident that the actual median household income lies between $50,147 and $48,149.

Now, how do the various towns compare to the county estimated? The way to tell this is to plot out the median household income estimates AND their margins of error and see where they overlap. When the county's overlaps with a towns, that means that they are, essentially no different. Technically it is safe to say that statistically we see no significant difference between the town and the county median household income.

On the other hand, where they do NOT overlap, that means that a town's median household income is either significantly higher, or lower, than the rest of county's as a whole. The graph below shows all of the town median household income estimates and their 90% confidence intervals.

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To make this a bit more understandable, I've drawn in red lines showing the 90% confidence interval for the county so you can more easily see how it overlaps, or doesn't overlap, each towns median household income 90% confidence intervals.

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Looking at the right side of the graph, note how the 90% confidence intervals for Lee, Deerfield, Marshall, Trenton, Marcy and Westmoreland are all above the red line depicting the top edge of the county's MOE. However for the twon of Western, while the estimated value of their median household income (the green box for Western) is above the county's, the confidence intervals overlap. This means it's possible that the numbers, in fact, could be identical ! So you'd have to say statistically that they are not significantly different !

On the left hand side you can see that Utica,  Annsville and Rome are all below the county median household income - they do not overlap, so therefore they are significantly lower than the county when it comes to median household income.

This same process could be done with any of the towns in order to compare them to other towns in the county. For example, what could you say about the Town of Trenton? What towns are not significantly different when it comes to median household income? Which are below them?

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Whenever you are looking at ACS data, you need to be aware of these margins of error and what they say about the estimates, especially in comparison to other geographies !

Speaking of Other Languages...

My last post was all about how you can see counties across the country where a significant portion of the population speaks some other language at home than English. There was a link to an interactive map where you could click on a county and learn a little about what language other than English is predominant there.

Below is a map of the tracts in Oneida County where at least 10% of the residents speak languages other than English at home. Since many of these areas are in either Utica or Rome, a second map appears providing a closer look at the two cities. Notice that there are several tracts in which more than a quarter of the population speaks something other than English at home, and two tracts where more than half of the population speaks non-English when at home.

Oneida County Map

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Utica-Rome Area Map

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Mapping Other Languages Spoken at Home

The Washington Post has a cool map on its website showing counties in the US where at least 10% of the population speaks something other than English at home. If you click on the map below, you can see that most of the counties where this is the case are in the southwest portion of the country, with pockets in the northwest, in Florida and along the northeastern seaboard. Oh, and then there's Oneida County in upstate NY !

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If you go to the interactive map you can click on a county and learn a little about what language other than English is predominant there.

Moonlighting in the 21st Century: Multiple Job Holders By State

Multiple jobholders are those persons who report that they are wage or salary workers who hold two or more jobs, self-employed workers who also hold a wage or salary job, or unpaid family workers who also hold a wage or salary job. According to the Bureau of Labor Statistics in 2009, 7.3 million workers held more than one job, and the multiple jobholding rate—the proportion of total employment made up of multiple jobholders—was 5.2 percent. 

Both the number of multiple jobholders and the rate of multiple jobholding have been stable in recent years and remain below the levels recorded during the mid-1990s. Among most of the major demographic groups, “moonlighting” has become less common in recent years compared with the mid-to-late 1990s. Who moonlights also varies widely, as shown in the graph below from BLS.

The multiple jobholding rate reached its most recent peak (6.2 percent) during 1995–96. The rate began to recede and declined to 5.3 percent by 2002. From 2003 to 2007, the multiple jobholding rate held steady and never returned to its high. Since the start of the most recent recession in December 2007, the multiple jobholding rate has hovered around 5 percent.

Multiple jobholding rates for most of the major demographic groups—men, women, Whites, and Blacks—have exhibited a similar pattern over the 1994–2009 period.

During the 1990s and early 2000s, the multiple jobholding rates of men and women were similar, but since 2002, the gap in rates between men and women has widened as men have worked multiple jobs at a lower rate than women have. In 2009, the multiple jobholding rate for women (5.6 percent) was higher than that for men (4.8 percent).

Among the major race and ethnic groups, Whites were most likely to hold more than one job. In 2009, the multiple jobholding rate for Whites was 5.4 percent, while the rates for Blacks and Hispanics were 4.8 percent and 3.3 percent, respectively. The rate for Asians was 3.2 percent.

The map below shows how multiple job holding varies across the country, with much higher concentrations (most likely the result of heavy farming activities perhaps?) in the central and upper midwest states.

Envisioning Migration Between States: Restless America

Chris Walker, of vizynary.com, spends a lot of time trying to help tell stories with visionary looks at "big data". In his article, Restless America, he shows us how migration patterns vary with an interactive graphic that allows you to "mouseover" a state to see the number of people moving between your selected state and other states.

Thicker arc lines mean more people moving. States are linked only if at least 10,000 people moved between them. If a state does not appear in the graphic, it is because it did not exchange at least 10,000 people with any other state in 2012.

To use the actual interactive graphic, visit the Restless America web post.

A Historic Look at Inflation Adjusted Minimum Wages

New York State just increased the minimum wage for it's workforce from the federal standard of $7.25 per hour to $8.00 per hour. For a look at the hard data behind the historical changes in the minimum wage, visit the US Department of Labor website, or for a more graphical view, here's a chart from theatlantic.com that shows how the historical data compares when adjusted for inflation to 2012 dollars.

State and Federal Prison Populations in the US

According to the graphic below from Governing.com New York State has seen a substantial decline in its combined state and federal prison population over the last decade. From 2000 to 2010, the total prison population dropped about 20% in New York State, from roughly 70,00 to about 56,000. You can also see in the graphic that the prisoner population dropped between 2009 and 2010, as well.