The U.S. Department of Education has a link on their website to The Equity in Athletics Data Analysis Cutting Tool, which allows visitors to download spreadsheets that show financial information about equity in college athletics. The universities that the data accounts for are US college universities that receive Title IV funding. What that basically means is that these colleges participate in federal student aid programs, which a majority of college universities do.

Considering that I was a rower in college, I was pleased to find this data. I was particularly interested in seeing what it would look like if I mapped out the college universities that have rowing programs and then by using proportion symbols, I could see which colleges had the biggest revenues. The following map displays revenues of collegiate rowing teams for both male and female programs combined in 2007:

(Click Finder! to view the data set)

Now to give you an idea of what each college rowing program revenue looks like by gender, the following map is broken down by female revenue and male revenue using proportion symbols to show the amount of revenue comparatively.

(Click map or Maker! to view map)

Popularity: 17% [?]

Global economic crisis! Record level unemployment in the U.S.!

With our latest dataset on unemployment levels for select countries from 1995 to 2008 from the U.S. Department of Labor, I decided to take a look at what has been happening to unemployment in this economic environment.

The next three maps show unemployment levels for three different years at the same scale.

Then too see the more short term effects of the current crisis on unemployment rates, I made a map based on the percent change of unemployment rates from the first quarter of 2008 to the third quarter of 2008.

It is clear that globally things have worsened since 2000, however they still have not reached the levels seen in 1995. Also, the U.S. still has much lower unemployment rates than many European countries, such as Spain, France, Portugal, Germany, Greece and Italy (this may change with the latest figures for the fourth quarter of 2008).

Although comparatively, the U.S. has lower rates of unemployment than many European countries; it is important to note that the U.S. has a much less significant safety net for the unemployed (in the area of health care for example) so that the social effects may be as devastating.

The U.S. is also one of the countries that has seen the largest percent increase in unemployment rates since the beginning of 2008. Only Spain, Portugal and Ireland have had larger increases in unemployment rates than the U.S. (Italy does not have data after the second quarter of 2008). Since this data is based on self reporting from each country, figures may be inflated or deflated, such as the case of the U.S. It is important to note that this data does not represent unemployment in poorer countries where increasing unemployment may be more devastating.

Take a look at these maps yourself or go to Maker! and make your own maps from the dataset.

Popularity: 9% [?]

In January, a record 4 million people are expected to gather in Washington, DC to take part in the Inauguration celebration. Hotels near the area sold out nearly the day after Obama was elected. Luckily, where traditional lodging failed, Craigslist saved the day. People all around Washington, DC (and I mean all around, including from places like Baltimore which is nearly 40 miles away) have been so kind as to offer up their couches, rooms, whole houses, and even offices to those in need of a place to stay for the event. That is, if you are willing to sell your first born child!

Prices for a room are ranging from $50 per night to above $4,000. It is quite common to see rooms rented for an average of $2,000 per night. In fact hundreds of DC entrepreneurs a day are jumping for the opportunity to make their month’s rent in one night of sleeping on a friend’s couch so they can rent their apartment. While the prices are often unbelievable, many offers include breakfast, a ride to the metro, and even babysitting.

We thought it would be interesting to see where these people’s room/homes were, if they were actually located anywhere near to the inauguration site (or DC for that matter) and how much they were charging based on their location.

We took a 3 day sample of ads from Craigslist, geo-coded them and then added some attributes based on prices and amenities. You can find this dataset in Finder!.

This first map shows the entire DC metro area and beyond to demonstrate the distribution of rooms for rent.

The next two maps show the DC area with rooms based on price per room, per night, as well as metro stops. It seems like there is very little relationship between the location of the room and the price. Go figure!

So if you are still looking for a place to stay, or if you want to check out how much you can get away with charging for your floor and a sleeping bag, check out this dataset in Maker!.

Popularity: 8% [?]

(maps made by Emily Sciarillo)

The question of who is allowed to purchase and possess firearms has been debated in state legislatures all across the country. Some want more restrictions and some want fewer restrictions, and every state has its own unique set of rules. Debates rage on and it seems that any amount of restrictions, high or low, will not keep everybody happy. Here, at Fortiusone we see ourselves as an unbiased party that simply wants to present facts. So we thought we would take a look into the heated topic and see if creating more restrictions was for the best, for the worst, or if it even mattered at all.

The first thing we did was create a dataset in Finder! that scored each state’s leniency toward the amount of restrictions put in place when purchasing and/or possessing a firearm. The dataset can be found here:

http://finder.geocommons.com/overlays/7897

We compared firearm restrictions on age, criminal background, and type of weapons across all states in the USA. We gave different point values for the severity of the restriction. Higher numbers were the result of tougher enforcement and lesser values were the result of lesser enforcement. A full rundown of how this point system was systematically determined can be found in the dataset description. The one important value that we obtained was a summation of all these different values for each state that we deemed the State Firearm Restrictive Value. The higher a state’s State Firearm Restrictive Value (the bigger the orange circle on the map) the less lenient the state was in their firearm restrictions. The map is below:

Now that we have this data we decided to pair it up with crime rate data across the country by state. The two areas of crime that we focused on were the amount of firearm related murders per capita by state and burglary rates per 100,000 inhabitants within the state. First we will look at firearm related murders. We decided to use this crime category because it gives us a great sense of the how serious firearm crime is in a state. The dark areas on the map below represent the states that display high rates of firearm related murder per capita.

The link to this dataset can be found at:

http://finder.geocommons.com/overlays/7902

and the map is below paired with the State Firearm Restrictive Values.

Now we will look at burglary rates (per 100,000 inhabitants) within the state paired with the State Firearm Restriction Values the map below. We decided that this would be a good category because it is often said that increases in gun ownership might lead to less burglary. Some on the other hand find this to be false. All in all it is another debatable firearm ownership topic that we can explore.

The link to the dataset can be found at:

http://finder.geocommons.com/overlays/7896

What can we conclude from observing the two sets of crime data with the State Firearm Restrictive Values? There is no show of a strong correlation in either case. When running a correlation formula between the data of firearm murders and restriction values you get a value of .1155888. When running the same correlation between burglary rates and restriction values you get a value of -.0144564. With values so close to zero it is easy to determine that a distinct correlation between the two values does not exist in either case.

Basically low levels of restrictions are found in states where crimes rates are high and also where crime rates are low. You can also find high levels of restrictions found in states where crime rates are both high and low. The results vary greatly. To conclude, it is perhaps wise to say that crime rates are not the sole factor when putting gun restrictions into state legislation.

Popularity: 8% [?]

Considering that the US produces 602.3 billion pounds of corn crop annually, I thought it would be interesting to map where most of our corn is coming from in the US. The type of corn, maize, which is the one most widely produced is a cousin to sweet corn that is a high-sugar variant. 99 percent of the US corn crop is actually the starchy, tough plant, known as maze. The following map shows the values, in metric tons (MT) of corn produced by each state. By clicking on a state you can see how much it produces.

If you are wondering where most of our corn is going, then here are a couple of the largest products of corn:

Feed= 333.2 billion pounds

Ethanol= 179.2 billion pounds

High fructose corn syrup= 28 billion pounds

Sweet corn (ears, canned, and frozen)= 5.8 billion pounds

Popularity: 7% [?]