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# What are the Odds of Succeeding with a College Degree?

June 5, 2012

Statistics lie, even when they relate to making choices in college.

Ever heard the math textbook definition of average or median? Both of these calculations are measurements of central location. Location might sound like an awkward word to describe a math formula, but it’s an accurate description.

When you hear “central location,” it probably makes you think of finding the middle of New York City. This is actually a good analogy for how averages work. To calculate an average or median, you need to collect a population of numbers. Then, placing all those numbers on a grid, you run an average or median calculation and you come up with the middle of where the numbers fall. It’s possible that the number you calculate may not even be one of the numbers you collected.

Another thought to consider: What does the middle of anything tell us about a whole? If the center of New York City were Central Park, could we then assume that all of New York City is a well-maintained urban park?

This runs contrary to our personal identification with the term “average.” We tend to think that we are average people. So when we hear a statistic that shows the average college graduate earning nearly twice what an average high school graduate earns, we expect that we’ll achieve the same outcome. After all, we are average people, so we’ll be earning the average wage.

How do we temper the misperception of averages and median data? Let’s say you rolled a die six times and it turned a 1, a 2, a 3, a 4, a 5, and a 6. The actual average/median of this outcome is 3.5. Does this mean the average person is going to roll a 3.5? Obviously, this statistic sounds silly, but also shows exactly how misleading these calculations can be. What if I said you had a one in six chance of rolling a 3? It changes your perception. That’s why today I’m going to give you the odds, not the averages, on succeeding with a college degree.

Odds of Earning the Median Salary

The Bureau of Labor Statistics (BLS) published a chart called “Education Pays.” It showed the median weekly earnings of a college graduate to be \$1,053 per week and those of a high school graduate, \$638. This type of statistic leads to the belief that if you go to college, you’ll earn nearly twice what high school graduates make. Is this a realistic expectation?

In real life, plenty of high school graduates out-earn college graduates. Just think of college dropout Bill Gates. BLS used a median figure, which really means that you have a 50/50 chance of earning more or less than \$1,053 per week. What were your odds of earning a median salary or more before college?

Georgetown University measured the range of income responses by college education. They found that 14.3 percent of those with a high school diploma or less earn as much or more than the median college student. That works out to a one in seven chance of out-earning the median college student.

Ouch. Unemployment for recent college graduates is almost 9 percent. That means 1 out of 11 college graduates are not earning a paycheck. Granted, this number is inflated given current economic conditions. However, the unemployment rate for those with a high school diploma is almost 23 percent, or nearly one in four.

While your odds of avoiding the unemployment line with a college degree is nearly three times that of high school graduates, you have to consider the fact that unemployed with no college cost is far better than unemployed after having paid \$12,804 per year for public tuition.

Odds of Striking it Rich

The top 1 percent of wage earners in the U.S. earn almost \$500,000 per year. The odds of anyone making it to the top are low, even with a college degree, but the odds are better than those with no college education.

Gallup conducted a study of its survey results to get a better understanding of how education and riches were related. Of those with college degrees, roughly eight in 1,000 make it into the upper echelon of income earners. For those without a college degree, the odds drop as low as three out of 1,000.

The Takeaway

Notice that success is not something out of reach for anyone of any education level. It also means that success is not a guarantee. However, what college can do is help increase your chances of success. For example, when it comes time to measuring up to median college wage earners, life hands the college student a coin to flip and a high school graduate something close to a die. Whether or not increasing those odds are worth it to you will depend on who you are.

JP is the author of the money blog My Family Finances, a site dedicated to helping families make wise financial decisions. He is also an MBA and works in corporate finance.

Tags:
colleges,
personal finance

I came across this incidentally and feel obligated to make a few comments.

Odds are a more intuitive way to communicate information, but it is not at all correct to say that statistics lie. In fact, it is that we do not understand what the value means that leads us to the problem. We assume things that are inaccurate about their meaning, and that is OUR fault, not the fault of the statistic. It would be the equivalent of an uncle being younger than his neice and saying that it is a lie that he is the uncle. He IS the uncle. It is our fault that we assumed he must be older than his niece in order to be her uncle. While usually the case, we assumed something that is incorrect. We were wrong, not his status as an uncle. The fact that we think a mathematical average might be expected for an average person is our own misunderstanding of what an average is.

The idea with central park is also a problem. Finding central park as the "middle" of New York would be the equivalent of finding the median of unranked values. You first must arrange the numbers in ascending order before you take the median (the median of 3, 80, and 5 is 5, not 80). This would probably set us in an apartment building, not central park.

I know this is not at all the point, but using statistics to effectively communicate science is my job so... When the data is normally distributed, the mean does exactly what we expect it to do. When we have extremely large or extremely small scores, the mean will be "misleading," in the sense that extreme scores will lead the mean far away from the rest of the values. In these cases, the median is a useful alternative. But no measure of central tendency alone tells us everything and this is why we use measures of variability such as standard deviation.

It could be the case that everyone who graduates from college earns EXACTLY \$1053 per week OR that half of earn \$0 and half earn \$2106. The mean and the median would be the same in both cases (\$1053), but in the former, the standard deviation would be 0, and in the latter, it would be huge (\$1053, in fact, assuming population values).

I appreciate your effort to point-out some of the places where people make errors and the attempt to correct these errors in our logic, but to say "statistics lie" causes people to mistrust them, when really they need to be educated about them.

The sentence: "What were your odds of earning a median salary or more before college?" should actually read "What [is the probability] of earning a median salary [of a college graduate] or more before college?" The "or more" means that this should be a probability, not "odds."

You also gave an average for debt from college. Inconsistent given your point AND something you have control over. Going to a cheaper school is easier than earning more.

(Also, I was hoping for a table or something that shows the earning rates for college graduates and non-graduates for let's say the top and bottom 5%, 10%, 25%...). Thanks!

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