Ground breaking research into the visual acuity
experienced by subjects while using beer goggles
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Furrow's Law was formulated one evening in one of our local brain storming facilities.
Furrow's Law was first presented to the public (well if you can call a bunch of Engineers and their lecturers the public) at the Department of Mechanical Engineering's 1999 Christmas Lectures.
It must have gone down pretty well as we were invited back to last year's Christmas Lectures. Thanks must be given to the members of The Mechanical Engineering Society, (The Force), for their tireless dedication to research which has helped me to acquire enough data to further the research this year.
The following research paper was brought to my attention. This paper includes some ideas along the same lines as those being explored in the Furrow's Law research (although obviously their research is no where near as advanced and well researched as ours): Muntling.doc
For Mr Ball, some extras:
Furrows law was named thus because of my very poor description (due to the effects of various fermented drinks) of the shape of the basic curve linking together a girl's actual attractiveness, the amount of alcohol consumed and her resultant perceived attactiveness - the shape of a furrow. This graph is shown below:
Research this year is taking place to determine the optimum time at which to ditch a current girlfriend. As everyone knows, 'the grass always looks greener on the other side of the fence'. This effect is manifested by hundreds of attractive girls suddenly popping up out of the wood-work as soon as you get tied down to one. To rub it in even more, they actually come up to you in night clubs and want to talk, go out for a drink, etc.
There are certainly reasons behind these effects. The list below gives a couple of the more obvious:
The skill of pretending to have a girlfriend while out on the pull is an area which will provide rich rewards for those able to master this tricky technique. (nb. The author is currently working on this technique, although he is failing miserably, basically having forgotten what it's actually like to have a girlfriend - any pretty girls who would like to help furthering the knowledge of science please don't hesitate to contact the Research Group at the email address shown at the bottom of the page ;-). Professional theatrical training could be a way forward, or a casual relationship (which is also know to work).
The question which goes through everyman's mind is whether they will be able to take advantage of the sudden influx and interest exhibited by these women (but beware, as soon as you dump your current girlfriend and your attitude towards the new girls changes you may find that they all evaporate).
Assuming that there has been a real influx of women (start of term at University for example), how do you decide whether to upgrade?
The following areas have therefore been investigated in detail
Comparative rating of girlfriends
There are many types of girl, with many positive and negative attributes. Thankfully my PhD is involved in determining metrics for the comparison of just such data (although my PhD is actually to do with Vehicle Driveability, the techniques are equally applicable). Some applicable metrics include the following:
These metrics need to be weighted and then combined to produce an overall ranking (an example of this method is illustrated in this research paper). I am currently preparing a questionnaire style sheet which can be printed out and used to rate your current girlfriend - providing for extremely fast calibration of your particular rating weightings.
The following table shows the industry standard method for weighting the various attributes of your girlfriend:
Statistical method for determining the best time to 'get rid'
Assuming that once you have dumped a given girl there is no way of getting her back, this problem can be attacked in a strictly mathematical fashion to produce an exact solution.
We must also make a couple of extra assumptions for the simplified case: that the metric which is to be ranked is distributed normally across the population space, and that the person making the judgments (that's you) has no prior information as to the average and standard deviations of this metric in the population (i.e. you don't know what the average attractiveness is, not do you know how good or bad it gets)
For this case the method is as follows:
This method is the optimum solution to what is called the 'secretary problem' or the 'dowry problem'. The reference for this work is: To be added soon
As I indicated above, this is a somewhat simplified solution. Generally you have some idea as to the max/min and average attractiveness of the population. It should also be noted that the distribution may not be normal, it may be skewed in either direction (for example I would expect the distribution to be skewed toward a higher average if I worked for Agent Provocateur - my application is in the post - and skewed toward a lower average if I worked in a coal mine).
If you have any ideas related to the direction and scope of the Furrow's Law research please feel free to contact the Furrow's Law Research Group at the following email address: Simon_Pickering@hotmail.com