Tag Archives: Charts

Earnings and Unemployment by College Major

The Wall Street Journal recently published a table of income and unemployment data  that presented pay and employment rates for various college majors. The original study by Georgetown University’s Center on Education and the Workforce contained enough additional details that I thought it might be worth trying to incorporate the information into a Tableau visualization.

After a little data massaging, I created charts for both the high-level fields of study and the more detailed individual majors. Each level contains unemployment rates, income levels, and popularity of major measured by number of enrollees.

One of the first things you notice is that, despite frequent claims to the contrary, college graduates with a degree in Education have the lowest median earnings overall. The Education field also has the narrowest range of income and includes four of the ten majors with the lowest median earnings. On the plus side, fifteen of the sixteen Education majors have (or had at the time of the study) unemployment rates below 5.5% — the weighted average rate of unemployment for all majors in the study.

Graduates with an Engineering degree have the highest median earnings overall and a relatively low unemployment rate compared to other disciplines. In addition, seven of the ten majors with the highest median earnings were found in Engineering.

Other majors with good earnings potential included the usual suspects (Computers & Mathematics, Health, and Business) while the best employment prospects were found in Education, Health, Physical Sciences, and Agriculture & Natural Resources.

As for individual majors, the winners in my completely fictitious categories are as follows:

  • Most Popular –  Business Management & Administration takes this category with nearly 2.8 million grads holding this degree. The next two majors in line (also in the Business field) weren’t even close — trailing by over a million people.
  • Best Prospects –  Actuarial Science beat out four other fully-employed competitors by coming in with a median income of over $80K.
  • Worst Prospects –  Clinical Psychology tops this category with an estimated unemployment rate of nearly 20%. Yikes! I also noticed that a number of other majors in the Psychology field had unemployment rates above 10%, which means that intra-discipline career changes for people with this major would be difficult.
  • Most Deceptive – The “winner” here is Architecture, an outlier with the lowest median earnings and the highest unemployment rate of all of the Engineering majors. For this category, I wanted a relatively popular major with an uncommonly high unemployment rate … the kind of major that churns out grads and then strands them in the unemployment line. An educational Judas, if you will. (Full disclosure: I have an Architecture degree, but I can’t say I wasn’t warned.)
  • Hidden Gem – I’m going to call this one a tie between Petroleum Engineering and Pharmacy Pharmaceutical Sciences & Administration. Petroleum Engineering has a slight edge on median earnings ($127K vs. $105K) but the Pharma major has a lower overall unemployment rate (3.2% vs. 4.4%). You probably can’t go wrong with either one but keep on eye on the horizon … Petroleum Engineering is notoriously dependent on the boom/bust cycles of the oil and gas industry while workers in the pharmaceutical industry are facing major changes as companies try to adjust to globalization and increasing costs of product development. 

Unemployment vs. Underemployment

The Bureau of Labor Statistics releases the results of two major surveys on the first Friday of every month (the Current Employment Statistics or CES and the Current Population Statistics or CPS). Although the amount of information in these two surveys is quite extensive, the general public is probably familiar with only a few specific metrics.

First and foremost among these is the unemployment rate, which represents the ratio of unemployed workers to the overall civilian labor force. As with anything involving the government, this simple number is more complex than it than it seems. For one thing, the BLS has no less than six different methods of calculating unemployment … and each one comes in a seasonally adjusted and unadjusted format. The standard unemployment rate — the one that makes all the headlines — is called U-3 and it is usually seasonally adjusted.

Many economists feel that U-3 is misleading because, over they years, it has slowly excluded many of the factors that used to go into how the U.S. reported unemployment. They prefer to use the “underemployment” rate or U-6, which is the BLS’s broadest measure of unemployment.

The basic definitions:

  • U-3 – Total unemployed persons, as a percent of the civilian labor force (the official unemployment rate).
  • U-6 – Includes those people counted by U-3, plus marginally attached workers (not looking, but want and are available for a job and have looked for work sometime in the recent past), as well as persons employed part time for economic reasons (they want and are available for full-time work but have had to settle for a part-time schedule).

Keeping all of these terms straight can be difficult for the average person, so — despite Stephen Few’s objections — I have created a pie chart that attempts to explain all of the various relationships. The central pie shows the  basic division of the working age population into the civilian labor force and people who are outside of the labor force. Each subsequent pie divides these categories into smaller and more specific subcategories. 

The calculations for U-3 and U-6 can then be represented as slices of the pie:


Right off the bat you can see that there is a problem with some of the various categories. For one thing, there is an entire group of people who are listed as Want a Job Now but aren’t working and aren’t counted as unemployed. This category includes people who have been out of work for over a year and have officially fallen out of the civilian labor force. Although the U-6 figure includes a portion of this group, many critics still feel that this practice understates unemployment.

Another way to show the calculation of the two metrics is graphically, using the color coding of the legend from the chart to show the details for each metric:

This excercise highlights another potential issue for measurement of the economy by showing the importance of the denominator (in this case, the Civilian Labor Force). Variations in this number have a tremendous effect on the outcome of both calculations. By reclassifying certain groups of unemployed (the Want a Job Now crowd), people are siphoned off from both the numerator and the denominator. The end result is a slight reduction of both the U-3 and U-6 rates. Not a big deal … unless you happen to be running for office.

Six Degrees of Joy Division

My local record store used to have this great poster on the back wall that explained how several dozen British indie bands from the 80s were all linked together through their various group members. The title of the poster was something like “Why All These Bands Sound the Same” and it was clearly a tongue-and-cheek slam of the gloomy post-punk sound of musical groups like Bauhaus and the Smiths.

I loved the design concept and looked for the poster when the store finally went out of business a few years ago. Although I never found it, it occurred to me recently that I might be able to reconstruct the graphic using some modern tools and data from the online music site AllMusic.com.

AllMusic is an outstanding musical resource and their meticulous site formatting allowed me to write a program that would crawl from page to page gathering information about interrelated bands and band members as it went. I decided to use the group Joy Division as a starting point because I liked the movie Control and had a vague memory of that particular band name appearing on the poster. The program ran over night … evaluating 37,538 separate pages before it completed its run.

Using the IBM visualization tool, Many Eyes, I created a network diagram of the bands that are within six steps of my “seed” group. The full interactive results are at the end of the post (worth the effort if the Many Eyes site is working) but here is a detail:

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The Joy Division Network

At nearly 38K records, this particular musical network covers a huge swath of Anglo-American rock-and-roll and includes almost all of the major groups in the Pop/Rock genre. What’s perhaps most interesting about this massive network is the fact that Joy Division is only linked to two bands directly, the acclaimed New Order (formed in 1980 after the death of JD vocalist Ian Curtis) and the Manchester supergroup Freebass (formed in 2004). All other connections are indirect, with a total of 20 degrees of separation between Joy Division and the most distant band in the network, post-grunge Los Angeles outfit Open Hand (formed in 2000).

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Other Thoughts on the Data

The first odd thing I noticed about the network was that, by focusing on the relationships between bands, the network excludes a lot of well-known solo artists. Even when these musicians joined a band, their independent careers limited these associations to one or two instances. The best example of this situation would be someone like Elvis Presley or Johnny Cash. Both of these artists were loosely linked together through a glorified hootenanny called The Million Dollar Quartet (along with Carl Perkins and Jerry Lee Lewis). The only other bands in this network are The Offenders and the Cash-related groups The Highwaymen and Johnny Cash & the Tennessee Two. Some of the other solo artists in this minor network are household names (depending on the household, of course), including Waylon Jennings, Kris Kristofferson, and Willie Nelson. Three bands, a half-dozen stars and a lot of hits … but no direct connection to the huge Joy Division network. Many current rap artists seem to fit this mold as well.

On the flip side, progressive rock groups like King Crimson had members who were in dozens of other bands. These social connectors can be seen at the center of a huge spider web of interrelated groups in the network diagram. Bands like these are often experimental in nature, with talented musicians putting their stamp on a number of different side projects. Some very influential artists can be spotted in the midst of these groups, including — using King Crimson as an example — famous journeyman players like Robert Fripp, Adrian Belew, John Wetton and Greg Lake.

Finally, although I distinctly remember the band Bauhaus and its associated constellation of bands (Love & Rockets, Tones on Tail, The Jazz Butcher, etc.) on the poster, they were not within six degrees of separation of Joy Division in the network data (they were about eight links away). This exposes an issue with my data gathering methodology because it doesn’t take into account other relationships between artists such as mentors, guest musicians, common producers or other ties. Still, it was an interesting exercise with fruitful results.

Additional Interactive Charts

Bubble diagram of musical styles (full band network):
Network diagram (six degrees of Joy Division):

Time-Distance Diagrams

After I was in a car accident a few years ago, I contacted the city Traffic Control Engineer to see if I could get a copy of the signal timing sequence for the intersection of the street where the accident occurred. The information they provided allowed me to construct a time-distance diagram to relate the path the car traveled to the 90-second traffic signal cyles for several streets. 

The time in seconds can be read down the side of the diagram and the distance can be read across the bottom. Stationary objects (like the traffic lights) show up vertically on the chart while moving objects cross the chart at different slopes depending on their speed. The blue line represents the path taken by a car which starts from a complete stop at one intersection and accelerates to a speed of 35 miles-per-hour in a very leisurely 9 or 10 seconds. Note that the line crosses the final intersection during a green light.

What I liked about this diagram was how easy it was to show a series of timed lights and the effects that different average speeds had on the outcome. I was reading Edward Tufte’s The Visual Display of Quantitative Information at the time and his section on train schedules was very inspirational. Despite my efforts, however, the other driver sued for injury and my insurance company settled out of court. Oh well, at least I was able to get this great chart out of the process.

Fighting Insidious Business Jargon with Design

One of the biggest barriers to introducing new concepts to people is that they often have old, preconceived notions about those concepts that are just close enough to the truth to cause confusion. For example, my company recently started a sales program that establishes performance incentives by “vertical” — one of those vague business terms that could mean just about anything to anybody. Tracking such an ambiguous concept can cause a lot of angst when someone’s paycheck is on the line so it fell to me to come up with some ideas to help clarify the definition.

The first problem I needed to address was the fact that most people already thought they knew what vertical meant. When you try and find a definition online, you’ll usually come across terms like “vertical industry” or “vertical market” which both refer to groups of companies that serve specific, related  industries (i.e. a niche market). In contrast, a “horizontal market” refers to companies that meet more general business needs.

The differences between these two definitions are pretty subtle and, as a result, most people tend to associate the term vertical with almost any industry, departmental function or even groups of occupations. In our business, we need to keep such categories distinct so I decided to create a matrix that placed our two main areas of focus — jobs and industries — on two separate axes. This would provide a simple visual cue to the differences during future discussions and presentations. The basic distinctions are:

  1. Industry (based on the NAICS standard) applies to a company or client.
  2. Occupation (based on the SOC standard) applies to a person or individual.

Unfortunately, a standard table would still present the information in columns and rows — leaving the vague association with “vertical” unresolved. To address this, I decided to take a cue from a common Scandinavian holiday decoration and rotate the table 45 degrees. This eliminates all vertical and horizontal lines in the diagram and forces the observer to abandon the concept altogether. In the diagrams, the industry information appears in the orange axis, while the occupation appears in the blue axis.

 

Once this basic structure is established, unique industry/occupation combinations can be “mapped” to demonstrate situations that are familiar to the audience. These examples help reinforce the concepts while emphasizing the difference between the two categories. It can be particularly helpful explaining examples where industries and occupations share some elements in their names (i.e. health services vs. healthcare practitioners).

A Switch in Time

Daylight Saving Time (DST) officially ends tomorrow and everyone in my little corner of the world will set their clocks back and get a well-deserved extra hour of sleep. We all know that this odd modern ritual is suppose to save energy (or candle wax or some such thing) but just how does it work?

First of all let’s look at what happens to the Earth’s day over the course of a year. Because the Earth rotates on its axis at a slight tilt, there are times where the North Pole leans toward the Sun (this is summer in the Northern Hemisphere) and there are times where the North Pole tilts away from the Sun (this is the Northern winter). A city or town located in the Northern Hemisphere experiences longer days during the summer because of the additional exposure it gets as it rotates in this position. The reverse is true for places in the Southern Hemisphere.

When you plot out the the sunrise and sunset times for different areas of the U.S., you can see that the daylight pattern varies depending on your latitude. Honolulu, one of the southern-most Amercan cities, has relatively static sunrise and sunset times while Milwaukee, located about halfway between the equator and the North Pole, shows more signficant changes in in the length of the day over the course of the year. In fact, during the summer months, this northern city gets nearly three more hours of daylight than the island paradise.

Things get a little weirder as you go farther north. The relative orientation of the Sun to the surface of the Earth starts to have a greater impact on the amount of daylight each area receives. Anchorage, which is located at about 60 degrees latitude, has six-hour days in the winter and almost 20-hour days in mid-summer. Barrow, located north of the Arctic Circle, starts to experience full darkness during the winter and 24-hours of daylight in the summer months.

Human civilization imposes a rigid structure on this natural daily cycle by setting up concepts like the work day, meal times, play dates and TV schedules. Of course, this structure only works if everyone’s schedule is the same so we’ve also developed things like alarm clocks, wrist watches and other timekeeping devices to keep us in synch. In some areas of the world (like Hawaii), the alignment of natural and societal cycles is fairly good. In other places it imposes some problems.

For example, a typical Milwaukeean who wakes up at 6:00 AM and goes to bed at 10:00 PM misses out on almost two hours of daylight during the summer mornings. However, if they adjusted their schedule to wake up at dawn during the month of June, they would be waking up 3-4 hours before the sun rises in December. By shifting the schedule by an hour during the summer months, Daylight Saving Time helps even out the daylight period in relation to the natural cycle.

The energy savings kicks in when you plot the additional amount of day time that some experiences during the summer. Presumably, this extra time is spent with candles unlit.

These charts also explain why Hawaii doesn’t use Daylight Savings time (it does’t experience enough variation in daylight to warrant the shift) and why some very northern locations may actually experience two sunsets in a single day (the time zone doesn’t quite line up with the natural cycle of the Sun).

Signs of Sanity

I dragged my family to the Rally to Restore Sanity and/or Fear in Washington, D.C. yesterday and we saw a lot of great signs. Some of my favorites also managed to bring in some chart humor:

The Huffington Post appears to have the best — or at least the biggest — collection of signs from the rally. A few of my favorites:

  • This one freaked me out! Where will I live?
  • Perhaps my favorite sign of the whole rally. What a great clash of immigrant tradition with Muslim sensibilities.