Mathematics of Dating

Latest revision as of 02:55, 16 August 2011

The mathematics of dating is a series of formulae of increasing comlpexity, designed to describe various variables involved in dating and romance.

[edit] Age and the Standard Creepiness Rule

The graph isn't exactly going to win artistic awards

The Standard Creepiness Rule states that if we define an individual's age as x, said individual should not date anyone under:

<math>\frac{x}{2}+7</math>

By extension, this equation then also defines the maximum age an individual can date:

<math>2\,(x-7)</math>

And similarly, a combined equation will demonstrate the increasing prospective pool as one ages:

<math>2\,(x-7) - (\frac{x}{2}+7)</math>

Now, this (boring) graph shows only the ages available. However does not take into account either the population of each age bracket (something which would require individual research), nor the percentage of those who are single in each age bracket.

It has been suggested however that graphing these equations will help boost your self-esteem, and generally give you something nice to put on your wall.

[edit] The Drake Equation

A commonly noted problem however is that environmental factors often decrease the ability of individuals to find someone with mutual interest; so that despite the fact that the estimated dating pool only increases with age, the experienced dating pool seems to be much smaller. Integral to this flaw in the equations is the shift of the 14 to 18 year highschool-oriented environment to an 18+ university/work environment, where age groups are unclearly defined, puberty has past, and mutual interests are less common - not to mention the increase in long-term committed relationships.

As such there are a variety of new variables to factor into any attempt at predictive equations, and thus we require a more detailed equation to handle this. The closest simile that currently exists is the Drake Equation.

The comparison between the Drake Equation's method for assessing intelligent life in space and the likelihood of finding a girlfriend was first made in 1999 in Germany, although was expanded on more recently (2009-2010) in the UK.

When applied to dating, the simplest (and most cynical) way of expressing the Drake Equation is probably as follows:

<math>G = N \cdot f_W \cdot f_L \cdot f_A \cdot f_B \cdot f_S </math>

Where:

<math>G</math> = The number of potential boyfriends/girlfriends

<math>N</math> = The current population total in your country

<math>f_W</math> = The fraction of the population that is male/female (generally around 0.49 for males and 0.51 for females, but can vary)

<math>f_L</math> = The fraction of the male/female population who live in your city

<math>f_A</math> = The fraction of the males/females in your city who are within the appropriate age range

<math>f_M</math> = The fraction of those who are not in a committed relationship

<math>f_B</math> = The fraction of those you find physically attractive

<math>f_S</math> = The fraction of those who you can actually enjoy being around

Effectively, what the equation does is establish population figures to work from, cuts down that population based on issues of proximity, applies the previously mentioned Standard Creepiness Rule to the proximal population, removes the portion of the pool who are unavailable and then applies personal taste (which may be a bit hard to quantify in exact figures, but standard practice would be to assume you're aiming for the "upper 25%" or 0.25 in each category - vary to taste).

[edit] Varying Proximity

Of course the equation as given above is limited to a very specific population. People travel, we have the internet, the population as given may not be wholly accurate to any given individual. Most of us know people overseas, or in other cities, and there are numerous vectors through which you can meet prospective new dating partners which don't conform to the model as given above. And most individuals are probably isolated from parts of the population in the above model as well, meaning that while it gives the dating pool for your city, it may not give your actual available dating pool for you as an individual.

Assuming it were possible to data-mine population figures based off degrees of separation from the individual concerned (ie, using some sort of Facebook application maybe), it may be possible to alter the Drake Equation so instead of being limited to "males/females in your city", it instead operates off "males/females within 2 degrees of separation" which is probably a more individually useful population to start from.

[edit] Extended Variables and the Pitfalls Thereof

The Drake Equation does actually give the room to be as specific as you want to be about the kind of partner you're looking for as well - the <math>f_S</math> variable can be expanded into numerous sub-variables of specific personal-taste traits assuming you can calculate the fraction of the preceding group which has such traits (in the UK example, this variable was "women who have a university level education", because that author felt that was the mental trait he was looking for most in a woman). This is not actually recommended, however.

Firstly, unless you are omniscient or a serial stalker probably you will not be able to ascertain whether any individual you go out with meets more than about three to six extra personal taste variables without prolonged interrogation.

Secondly, by being too exclusive or picky you are very probably limiting your own ability to find someone you'd actually be happy with.

And thirdly the bigger the list, the closer one gets to the Imaginary Person Threshold; whereby all individuals who actually exist have been excluded.

[edit] Sampling and Decision-Making

There is an alternative to being excessively specific however. Studies have demonstrated that in a pool of 100 candidates, the most sure-fire way of getting someone who best meets the criteria (for any given criteria) that you are looking for is to sample 37% and then pick the next candidate who exceeds or matches the best of the initial 37%. Of course in dating 37% is an insanely large number, but as proven by the equations above the dating pool is significantly larger than 100.

The same study demonstrated that if the pool of candidates increases to 1,000 then the required sampling size actually drops to 1-2% (10-20 people). If you have a degree which involves advanced statistical analysis, you can use the generated population size of viable candidates from the Drake Equation as expressed above to calculate an appropriate pool for deriving a statistically reliable sample size to establish your baseline from. For everyone else, 5-10 is probably the most reliable sample size regardless of specifically how big your supposed dating pool is.

After that, all you need to look for are people who you think exceed the expectations gained from the initial sample and you're probably dating some pretty good people.

[edit] The Sanity Clause

Of course the idea of having 5-10 "throw-away" dates to make a statistical sample is a little silly. If one intends to actually use the above, consider that (a) life surprises you and you may find the right guy or gal in the first 10 dates, and (b) if you don't, consider it a way of looking at past relationships to assess a good direction for finding future ones.

[edit] Conclusion

It is possible to use mathematics to both describe and guide dating practices. Whether an individual should use these methods to assess their situation is a personal decision and may vary depending on your level of sanity and your commitment to the field of mathematics. For average use, it is not necessary, but hopefully the above may serve to help shine light in corners previously unthought of.

[edit] Useful links

• http://joelgilmore.com/2011/01/relationships-and-facebook-part-1/ - Joel Gilmore has an in-depth look at dating status vs age based on facebook numbers

• Australian Population data by age (ABS)
• Australian "MARRIAGES, DIVORCES AND DE FACTO RELATIONSHIPS" (ABS)