Tuesday, January 30, 2007

Marriage Equations

It's been just over two years since I got married, and I remember thinking (amid the nearly debilitating fear that we would run out of alcohol at our mountain cabin wedding and thus trap our families in a scene from the Shining) that it would be wonderful to finally be free forever from the intrigue and confusion of dating.

You can't fault the optimism.

Now, through the lens of hindsight, I realize that I should have known that dating and even cohabitating were only warm-ups for the big dance. Example: I didn't really mind the eggshell color of our living room walls——it provided a functional backdrop to both the climbing/skiing pictures taken by a friend in Patagonia, and to the portraits of Italian cafes and riverboats Kristi's father painted, which we hang in place of the climbing photos whenever he visits. However, to Kristi, the color was "dead guy white." Let me also explain that we have rather complex crown moulding framing the stuccoed ceiling, making painting nearly akin in needed time and expertise to completing a PhD in particle physics. She wanted something "bright and cheerful, like a nice sunshine-pumpkin. Oh and blue trim." I really had no idea what I wanted other than not to paint the living room sunshine-pumpkin with blue trim. Needless to say:

And I should have known from the start. Why, I wonder, didn't I realize sooner the way the wind was blowing and just paint the darn thing, rather than creating relationship strife to the tune of then also needing to put a skylight in the upstairs bedroom? I needed an equation—something along the lines of "Is she really serious about that home improvement project?"

I thought, though, that before getting to this one, I would look at some more fundamental equations that govern marriage. In the equations below, the first is based on solid statistics—an 11,000-person study by the CDC that explored factors that help and hurt a marriage's chances of working (for example, they found that if a woman is married before age 24, her chances of staying married for 15 years decreased by 30%). These statistics were easy to write in math terms, and the equation does fairly accurately predict your chances of being married at time "T". Granted there are other factors that might help or hurt your specific marriage, but the CDC study found that, for most people, these are the biggest factors. Remember that the average for all marriages is only about 50% and if you get a low number, please accept my very best wishes in bucking the odds.

The other two ("should we get married" and "how many kids should we have") are a bit more shoot-from-the-hip. With this kind of equation, I try to make the math match common sense. If you put in honest numbers, they return honest answers, but they're not quite as scientific as the first.

So, good luck, have fun, and check out posts deeper in the blog for additional marriage-relevant equations.

What are the chances my marriage will last?

A= Her age at time of marriage
E=Current combined years of post-high-school education
K= Number of kids from this marriage
R= How religious is the couple (1-10 with 10 being “the Pope”)
D= Combined number of divorces of couple’s parents
P= Combined previous marriages
T= Years at which you are computing the chances

H.e.a. stands for “Happily Ever After” and is the percent chance you will still be married at time “T”

Should we get married?

T= How many years have you been dating?
L= The number of times per day that something makes you think of this person
C= If your families got together for a holiday dinner, the estimated number of times there would be uncomfortable friction
S= How many shared interests and/or goals do you two have?
A= How many individual or conflicting interests and/or goals do you two have?
D= The average number of disagreements you have with this person in a month

If Ttk is above one, you should tie the knot

How many kids should you have?

S= Your combined household salary
K= Combined, how many brothers and sisters do you and your spouse have (include yourselves in this number)
T= Combined hours per week you and your significant other work outside the house
A= On a scale from 1-10, the highest level of aversion you have to any of the following: Changing diapers, sleep deprivation, visiting in-laws, tantrums
E= On a scale from 1-10, how concerned are you about global overpopulation

Kids, of course, is the number of kids that your lifestyle supports.

Friday, January 26, 2007

Will We Invade Country X?

I originally wrote this for an interview on the PRI radio program Fair Game, but we got to chatting and ran out of time, so I thought I'd blog it.

Let me first say that I think it would be a lot of fun to invade Trinidad. While I mean no disrespect to Trinidad, I'm fairly certain it would not be an overly cumbersome task for the U.S. military (even extended as they are). And the exit strategy would be obvious: after Carnival, we come home. We could make it a yearly event—invade Trinidad, party for a couple weeks, and then bring the troops home. Talk about a morale booster! And not just military morale—the entire country could ride the wave of patriotic fervor, immediate military success, scenes of troops partying with the locals, and then ticker-tape parades when the troops return to the grateful nation.

I'm afraid, though, this good-natured drubbing of a small Caribbean party island is unlikely in the current political climate. At least historically, we have chosen not to invade countries like Trinidad. And notice the equation is not "Should" we invade country X, but "Will" we invade... Unfortunately, this "will" necessitates taking into account not only my personal bent toward invasion to the soundtrack of steel drums and camoflage that includes rasta wigs, but also the historical record of who we have and have not actually invaded, and why we chose these countries over others. Granted this equation is a bit shoot-from-the-hip, but the results are spooky (see below).

Will we invade country X?

L= In the past twenty years, how implicated in the loss of American lives has this country been? (1-10 with 10 being Afghanistan and 1 being Switzerland)
T= How totalitarian is the government (1-10 with 1 being Finland and 10 being North Korea)
G= In thousands, the Google hits when searching “sanctions against [country]”
N= In your opinion, the president’s opinion of this country’s overall WMD scariness (1-10 with 1 being Vatican City and 10 being Iran)
B= Enter 10 if this country is on the U.S. State Department’s list of states that sponsor terrorism
W= Enter 5 if there is a travel warning against this country
E= In millions, the barrels per day of oil exports
I= How important is this country to the stability of the region (1-10 with 10 being China, Russia, etc.)
P= Percentage of the population below the poverty line (if not in CIA fact book, enter 20)
$= In billions, the country’s GDP
O= Add the following: 5 if this country is a NATO member; 5 if it is in the EU; 2 if it is in the WTO; 10 if it is on the NATO Security Council.

If GwJoe is greater than 1, we will invade the country in question.

Data and Results (yes, some of the 1-10 variables are my subjective opinion):

As you can see (or maybe you can't 'cause it's so small—sorry), this correctly predicts invasion of Iraq and Afghanistan, with the only surprise being that we will also invade Haiti (driven by the extreme poverty). Also, Iran is quite close at .945, as is Sudan at .907. This equation also successfully predicts (retroactively) the invasions of Cuba, Bosnia, and Somalia.

Thursday, January 25, 2007

A quick note on methodolgy and legitamacy

In theory, if you could define all the factors that go into making a decision and could define exactly how important is each of these factors, and could define how these factors interact, you could make an equation that precisely solves any decision. Of course, to be perfect, this equation would have to be tweaked and amended to include the variables that are relevant to each person making the decision, and the framework of the equation would have to reflect their personal value systems, etc.

What a pain in the neck!

It's much easier (and funnier!) just to wink at the problem and shoot to mimic common sense as closely as possible with a minimum of variables. So that's what I try to do with these equations: match common sense, and hopefully provide a laugh. Will the equation provide the be-all, end-all answer to all of life's problems? No. But unless I miss some glaringly important variable (which I try very hard not to do—please comment if you catch something!) or somehow flub the math (which I don't think I've done yet, but I'm sure the day is coming), they should provide a fairly honest answer for the vast majority of people. And they're certainly much more accurate than that Magic Eight Ball you had in middle school!

It's like this: if you're deciding whether to walk, bike, or drive to work today, the most important variables are practicality and desire (do you want to and can you). I would probably break these up into time it would take, time you have, distance, how much stuff you have to carry, what the weather's like, and your physical condition. These "big" variables take into account a whole bunch of possible special situations. For example, we don't need a variable for "is your leg broken" because we already have a variable for "how long would it take you to walk?" Presumably, your reduced crutching speed would drive this equation toward driving : )

And once I've drafted an equation, I check it. No, I don't compare people using the equation to a control group in a controlled, double-blind test. Actually, I just pop the sucker into a spreadsheet and throw a bunch of test numbers at it, hoping that the results match common sense. "Whose common sense?" you might ask. Well, mine. And my dog's. He has a very good head on his shoulders. Unless he's around snow. Or water. Or other dogs. Or kids... Seriously, though (did I just write "seriously, though"? I sound like a cruise ship comedian...), the funny in these equations is in giving them to people who need a substitue for common sense. Look left; look right; if neither of these people needs equations to simplify their lives, it might be you.

So, the equations are logical and they "work". Meaning that if you put in honest numbers, they return honest answers—especially if you look over the list of variables and they look like the factors you would use in making the decision. But (wait for it...) you still have free will (or maybe you never had it in the first place).

And there are a couple equations I've written that are actually based on fact. Specifically, three:
1. For the Nov. 4 issue of Congressional Quarterly, I wrote an election predictor. Looking at past outcomes, I tried to figure out what variables were important to candidates in Senate elections (House was too local, and anything below Hosue seemed based on which grocery store the candidate shopped at). Admittedly, I incorporated much shoot-from-the-hip math and personal conjecture, but the equation batted in the low-mid 90% range (with 100 Senate seats, I'll bet you can do the math). Also admittedly, I got lucky. Who knew Tester was gonna win in Montana, that George Allen would fall in Virginia, and that Robert Menendez will rock it in NJ? I certainly didn't, but luckily the equation predicted each (though it flubbed Nebraska—how does a state that red elect a Democrat?).

2. For John Tierney's column in the NY Times, I wrote a lighthearted equation predicting the duration of celebrity marriages. Plugging in the numbers you could decide in percentage the chances a couple would be married at time "T" in the future. It matched historical data pretty well, and we'll see how the predictions play out.

3. For Good Morning America, broadcast January 31, 2007 (yes that's this coming Wednesday), I wrote the real-human equivalent of the celebrity marriage equation, and tried to put a percentage on "how long will your marriage last?" Granted this is a loaded question. Without getting too geeky, I looked at an 11,000 person study by the CDC (www.cdc.gov/od/oc/media/pressrel/r020724.htm), which dropped in my lap the factors that help and hurt your chances of staying married. For example, the study showed that if a woman gets married before age 24, she is 30% less likely to remain married for 15 years. This is easy to express in math. So, this equation is pretty solid, but, like the celebrity marriage equation it only offers a percent chance—if you come out with a small percentage, my very best wishes in bucking the odds. As a side note, the other two equations in this broadcast are MUCH more subjective—yes, they are logical and fun, but they also could have been presented with a larger grain of salt.

So, I hope you look at this blog and at these equations and evaluate them for yourself—how close to an honest decision do YOU think is in the math? I'd estimate most at around 80% But most of all, I hope you enjoy.