This fact doesn’t seem fun at all.
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Beat me to it. The statistics say you should care. Whether you want to is up to you.
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Correlation =/= causation is not relevant here.
Whatever causes promiscuous women to have higher risks of divorce is correlated with promiscuity. Not marrying a promiscuous woman will thus reduce the risk of divorce (Even though I don’t necessarily know why female promiscuity and divorce are correlated).
Had I said that teaching women to not be promiscuous would reduce the risk of divorce, a complaint of correlation =/= causation would be relevant.
Ice cream sales are positively correlated with the risk of drowning. But I can assure you, eating less ice cream does not reduce one’s risk of drowning.
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As I said, reducing promiscuity wouldn’t necessarily reduce divorce. But the goal is not to reduce the amount of divorce, only the amount of divorce that happens to you.
The correlated variables either have a causal relationship or they don’t. Thus, any risk reduction that would accrue to an individual would have to be reflected in a risk reduction for the population at large.
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You aren’t trying to cause something. You are just picking based on incomplete information and hoping to get the result you want. For those purposes, correlation is sufficient.
I give you one million pieces of paper with numbers 0-10 on the front. On the back of each is written “divorce” or “no divorce”. I tell you that the probability a paper says divorce on the back is given by the graph in Verne’s link and the number on the front. If you can’t look at the back but want to pick a paper with “no divorce” on the back, you should pick a paper that says “0” on the front. This is elementary probability.
Admittedly, there are many mitigating issues such as:
–the cost of overemphasizing sexual history in your selection process at the expense of other important criteria
–the degree with which we accurately know sexual history
–the effect that a man has on the probability of divorce
–the effect that attaching significance to sexual history might have on divorce probability
–whether certain men are better matched with high n women even though most men are not
i would have declined so fast. after about hearing about all that history of STI’s i would have just stayed away from the chick forever.
i also read online awhile ago that there were untreatable strains of gonorrhoea. STI’s and STD are no joke.
yall make sure to be careful if you guys are hooking up with random chicks/dudes. wrap it up.
With more marriages ending in divorce than not, doesn’t that mean that, if you want to avoid divorce the best way to do so is to not get married?
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I worked in a majority Muslim country for a while and the double standard is real. I had a guy tell me that he would never marry an “unclean” woman who had slept with somebody before marriage. Not a big deal, except for the fact that he had a hooker sitting on his lap that was a different girl than the night before. Hypocritical much?
There’s also a big thing where the girls have anal sex to preserver there “virginity”. Or where girls get surgery to be a virgin again. I’m very grateful that I don’t live in a country with those types of social stigmas.
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Similarly: I give you a million pieces of paper with ice cream consumption data on the front. On the back of each is written drown or don’t drown. I provide a link to data indicating the positive correlation between ice-cream consumption and drownings. If you can’t look at the back but want to pick a paper with don’t drown on the back, you should pick a paper that has a low ice-cream-consumption value on the front. As you say this is, indeed, elementary probability.
The question is, do you think the above demonstrates that an individual can reduce their risk of drowning by refraining from ice-cream consumption?
Just to be clear, I am not arguing that there is no causal linkage between pre-marital promiscuity (for lack of a better term) and the likelihood of divorce (despite the fact that the data presented in the link are far from unambiguous in this regard).
Edit: Let’s get some expert input here. @ActivitiesGuy, if you don’t mind?
The difference between ice cream and promiscuity in this example is that it’s unclear (to me at least) what the pieces of paper represent with ice cream. Are they days or locations or something else? If they are days, I can’t well pick and choose which days to be alive. Locations-- I might well be able to avoid going places with lots of ice cream and reduce my risk of drowning.
This does bring up the fact that if I better understand the cause I might be able to collect different data that is more highly corellated. For instance, Verne’s article suggests n might be a proxy for religious dedication to certain religions. If that is true, finding out religion might be more useful.
It occurs to me that there is a way whereby the data doesn’t help men make a choice. It is possible that some characteristic of men that reduces the risk of divorce is more common among men that marry low n women. If this is the case, a given man changes nothing by deciding based on n.
It’s total ice cream sales (or consumption in gallons) on a given day in the US. The higher the number, the greater the likelihood the other side of the paper says drown.
Not getting married is the easiest way to not get divorced, and it always has been regardless of the percentage of marriages that end in divorce.
Then what does picking a piece of paper correspond to in real life? I can’t just choose to not be alive on certain days and be alive on other days. If I could, yes, I could reduce my risk of drowning.
Also of note, I would need a way to predict ice cream sales beforehand.
My joke is less funny when you explain it 
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It corresponds to whether one elects to eat ice cream (or not).
You assume the people eating the ice cream are the people drowning. No data supports that.
On the other hand, the promiscuous women are the same women getting divorced. That data says that explicitly.
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Man, this blue section down here really produces some of the strangest discussions.
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