How much are we “into” NATO? Check the Data!

picture1There has been much discussion about whether or not we should restructure NATO, given the change in defense posture and the ever-growing “nation agnostic” threats that currently exist such as ISIS, cyberthreats, etc.  Given that we are part of NATO (since 1949) and that we conduct joint exercises in Europe, as well as contributing to the defense of Europe, we should probably know how much we have invested into the organization.

The chart below depicts the percent that our defense expenditures contribute to the NATO defense posture.  As you can see, we have NEVER contributed less than 56% of the NATO budget, although these data did have some differences based on NATO financial reports in different years (mainly because of different definitions of NATO vs NATO/Russian contribution).  However, I took this data straight from the NATO documents depicting the financial figures (http://www.nato.int/cps/en/natohq/news_127537.htm).

nato-contributions

US Defense Contributions to NATO (See citation in text)

What does it all mean?  If you take a look at the US contributions vs European contributions you see a gradual increase in most countries contributions, but most come from the US.  It might be time to reduce our overall expenditures in this arena and have the Europeans take on more of the cost.  Germany seems to be coming up to speed, but given their stature in Europe as the center of economic development, it would seem they could become the main contributor, along with France, Spain, and Italy. Fair contributions based on nation involvement seems to be the best way of equalizing the funding of this very important organization but that is said without any real background information or political/economic information on why we have contributed so much to NATO.  This data speaks only on percentage (which incidentally runs in the billions of dollars per year).

The NATO council would have to meet and discuss a plan for future joint defense planning including resources that accompany this plan.  Until then, we will continue to contribute to an organization that has been a major part of the defense of Europe and has grown since the breakup of the Warsaw Pact (NATO’s original foe).

But in the meantime, the data presented shows a distinct difference between the US and European nations in defense contributions to an organization that entails the “North Atlantic” not just the US.  Maybe it is time for NATO to reorganize and restructure to better meet the future need of European Defense.

Learn, Offer, Value, Educate (LOVE)

Numeric Hysterics – Ask The Right Questions!

crazy-numbers

 

I have seen so many numbers being thrown around the press lately with little explanation of those numbers.  The numbers are given in headlines or headers that are accompanied by a narrative that incorrectly concludes what those numbers represent or – worse – no narrative that lets the uninformed observer make their own conclusion.  A few examples are necessary in order to further illustrate this very concerning trend.

I was reading in a newspaper that Social Security was receiving a .3 percent increase.  After seeing that, I talked with a few people about the article in different venues, asking them the amount of the increase.  Their response — 3% increase.

I explained that figure was wrong, and that it was in fact POINT 3 % increase.  They looked at me and stated that it was the same.  I explained that a 3% increase meant that for every $1.00 there would be a 3¢ increase.  Again, they said that is the same as POINT 3% increase.  I further explained that a POINT 3% increase meant that for every dollar there would be a .3¢ increase!  In other words, it would take 10 TIMES that increase to make the 3% increase that people think they are getting.  Remember that 3% is the same as saying .03 and .3% increase is the same as same .003.

Well, that is one simple case of incorrect conclusions, but the other one is much more serious.  It entails that percentage of police stops of minorities vs non-minorities in Baltimore County, Maryland.  According to a televised segment, there was a horizontal bar graph that showed that 56% of stops in Baltimore County were made against minorities.  With just a slight explanation, and more editorial comment, the narrator stopped short of explaining in detail where this information originated or what it really meant.

In order to really understand the data, several questions must be asked:

  1.  Where were the stops done (area of the county)?
  2.  Why were the drivers being stopped (warrants, tail lights, speeding)?
  3. What is the percentage of minorities in the area where the officer made the stop?

I list these questions because what the horizontal bar graph presented was just one perspective of the data — the number of stops made and to whom was stopped.  There are questions as to where and why that are not answered by these data.

A more telling data set might have been if the officer gave warnings to non-minorities but not minorities, or if the officer pulled the driver over after they identified the race, but I did not see any of these questions in the bar graph on the screen.  I just saw a graph that (without further description) showed that Baltimore County Police Officers treated minority drivers worse than non-minority drivers.  Without further explanation, or some more specific data, this is not only incorrect, but potentially damaging (guilty before being proved guilty).

There are situations where statistics can help.  A study completed by three researchers partnered at three prestigious universities included jury pools from counties in two states and did a series of statistical testing on these data points.  Their study is both extremely informative and contains a number of developed hypotheses (questions) that were explored and tallied.   I will not go into the conclusion since it is not the conclusion that is important (although well worth the reading of the study), but the lengths to which the students went to study the data, not just present it in its “naked” state.  You can see the study at: http://repository.cmu.edu/cgi/viewcontent.cgi?article=1349&context=heinzworks

So what do I wish to achieve from this article?  I want to point out two very important points:

  1. STOP presenting data without studying that data for spurious conclusions and indicators
  2. ASK the right questions concerning the data so that there is appreciation of what that data REALLY shows

In this day and age, we are prone to take extreme steps without a real representation of what a graph means and how those numbers affect not just us personally, but what they say about us as a collective.  We need to take each data set and question it to the point of getting to the truth.  Only then can we swerve away from numeric hysterics.

Learn, Offer, Value, Educate (LOVE)