“Cheating people of their money is the fastest and easiest way to get rich.”
- Anonymous
Do you think that the above statement is true? Though one would never resort to cheating because of the legal issues involved, many would think that cheating is in fact the easiest way to get rich.
In the following text, I will be exploring deep into this concept and help you determine the “benefits” in cheating.
We will begin this by using a standard example of a cheater. Betting on dice throwing has been quite a popular game ever since the invention of a die*. As such, the dice game example will used here to create more relevance to our world:
*Two die put together is called dice.
“In 100 games, my opponent needs to win at least one game for me to have a loss. But his probability to win for this particular toss is 0.01. How can he win me?
Even if he wins for this toss and caused me to have a loss of $ (Loss - profit) = $ (120 – 99) = $ 21;
After another 100 games, I will make a profit of $ (100 – 21) = $ 79
And to make me lose again, he will have to win yet ANOTHER toss with probability 0.01.
By this logic, for 10000 games, he must have at least 83 wins.
This is because 83 wins for him generate $ (120 * 83) = $ 9960 and my profit then is $ (10000 – 83) = $ 9917.
But the probability for him to win for
each of these tosses is 0.01. It is
hard for him to win even in a single toss. Let alone 83 times!!
Thus the more games I play, the more I will win and less likely that I will lose.”
At first sight, his explanation is very tempting for us to follow. For a majority of us, we might even actually believe in him~!
However when you apply simple mathematical equations of probability to this problem, you should clearly see why you should not believe in him:
Probability of 0.99 in winning means Winning 99 games out of 100, he will still lose 1 game.
Thus he should lose $ 21 each time he plays 100 games. It does not matter how many times of 100 games he plays. As long as he plays 100 games, he should lose 1 game.
For example, if he plays 10000 games, he should lose 100 games. (1 percent of 10000)
Hence, his total loss is $ (120*100) = $ 12000 which is greater than if he wins all 10000 games.
In this scenario, he will always lose. If you still do not understand why, take a look at the table below. Through a Gambling Simulation Program I’ve created, I ran a sequence of trials of “N” games 6000 times and recorded the readings.
Number of Games |
Number of final Winnings |
Number of final Winnings |
Total Number of |
30000 |
2 |
5998 |
6000 |
20000 |
34 |
5966 |
6000 |
10000 |
214 |
5786 |
6000 |
5000 |
599 |
5401 |
6000 |
2000 |
1349 |
4651 |
6000 |
1000 |
2105 |
3895 |
6000 |
100 |
2183 |
3817 |
6000 |
50 |
3758 |
2242 |
6000 |
10 |
5593 |
407 |
6000 |
1 |
5984 |
16 |
6000 |
From the table, if 30000 games are played, out of 6000 times, there are only 2 times where he might win eventually. This clearly shows that if he were ever to play 30000 games in all, he will most likely lose rather than win. On the contrast though, especially for small number of games (eg: 1 game), he should be able to win, but the amount he is going to win is minimal compared to if he actually loses. Thus though the probability of him winning is very high, he should not play at all.
In other words, though the chance of him
succeeding in cheating is very high, he should not go around cheating people.
This is because, the more he cheats, the more he will lose.
In conclusion to this lesson, I hope I’ve
brought light to everyone, including those who have been cheating people all
their life. Cheating is not a right thing to do and it will not bring you much
benefits. Instead you might suffer the consequences of your wrong doings. Remember
that you will always reap what you sow……..
Extras:
For those of you who would like a sample of my Gambling Simulation Program, you may download it here.
# Note: This file is for use in Java
environment only
*Any unauthorized usage of materials found on this website is in violation of the copyright law and might
result in an official lawsuit against you*