Math tips on when to stop looking for a better partner!

The book how long is a piece of string by Rob. Eastaway and Jeremy Wyndaham makes interesting and amusing reading. It is what it says it is: The hidden mathematics of everyday life.

I found it fun to read. Let me give an example from the book. There is this chapter on how to maximise your chances of ending up with the most suitable partner. Selecting the best partner can be tricky as one does not meet all potential partners at the same time. Even in an arranged marriage system it is not always possible to keep one side waiting because they will be seeing other people and delaying tactics could mean losing out. But a decision has to be made even though there is no way of finding out who or what is coming next. The authors have compared this decision (of selecting a partner) to other decisions like finding the right apartment or the right job. Each of these choices come to us one by one. If an offer is rejected there is often no way of going back. So when does one stop looking? The way this book explains it might sound a little cold-blooded but it’s amusing all the same. And well, many people do keep waiting until they find the “best.”

The authors give an example of a man. Let’s call him Rajesh. Rajesh has ten girls lined up. He knows that he is a good guy, reasonably good looking and with a good job. He knows that at least a couple of these girls will say yes to him. But who should he say yes to? Suppose he says yes too early he could lose out if someone better comes along!

Let’s say he meets the first girl, Reena. He finds her okay but the chances of her being the most suitable of the 10 are just 1 in 10. But if he says Yes to the first girl who is “better” than Reena, perhaps the second one he meets, then he increases his chances (of ending up with the best amongst the 10) from 1 in 10 to 1 in 5.

Rajesh can always keep rejecting girl after girl, hoping that the next one will be “better” than the previous but there are strong chances that somewhere along the line he might say no to someone who is the most suitable of them all. So this is a risky strategy. The “better” person may have already come and gone! Ofcourse, there is a chance that the last one is the best but that’s a slim chance, only 1 in 10.

So what the authors are saying is that if someone has the possibility of meeting 10 potential partners then they can  improve their chances of getting the best if they choose the best of the first three they meet. This way, mathematically, there is the highest chance of them ending up with the “best” partner. The authors admit that there are flaws in this plan because there is no way of knowing exactly how many potential partners you will meet in your life, but according to their calculations a person should settle down after meeting about 37% of  the potential partners. If this is not done, then the likelihood that the “best” partner has passed by keeps increasing. Finally you reach an age beyond which you have told yourself that you cannot wait (for marriage) and you have no choice but to choose the last one.

The authors have demonstrated that this works by experimenting with a blind date game!

Another interesting chapter in this book is on how conmen get rich. Simple mathematics is used to fool people. The authors give an example of a football scam. I’ve changed the example to cricket.

The conmen send an email to Mr. Kumar and tell him that the Rajasthan Royals are going to beat the Mumbai Indians that day at the IPL and ask him if he would like to subscribe to their predictions for all the IPL matches. Mr. Kumar is skeptical and deletes the mail, congratulating himself on how he has managed to see through this scam. But well, the Rajasthan Royals does win and then Kumar gets another mail, this time predicting the win of the Delhi Daredevils against the Kolkata KnightRiders. When this comes true Mr. Kumar tells his friends about this, but even then he does not subscribe. After all, this could be sheer luck. But the emails continue, and each time the prediction turns out to be correct. All in all five emails are sent and Mr. Kumar is finally sucked in. He subscribes by paying a designated amount.

Everyone who has received these correct predictions may not subscribe but even if one in a hundred does the scamsters have made money.

The way it’s done is simple. Thousands of similar emails are sent out, half of them predict a victory for one team, and the other half victory for the other team. Then the next email goes out to only those who had got the correct prediction….and so it continues until at least about a hundred people have received correct email predictions at least five times. Out of these hundred the chances are that a couple of people will pay the amount and subscribe!

The book has some other interesting workings, like that of a taxi meter and it explains why weather forecasters are often wrong, and the patterns behind a hit single. All in all 16 chapters, each dealing with something different. A good book to browse through!

(Photo is by me and copyrighted)

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