A INTRODUCTORY LESSON ON

WHY YOU SHOULD NOT CHEAT

 

“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.

 

 


A man who is very experienced in cheating has just found a way to earn an infinite amount of money. He has just created a bias die with the probability of a “1” appearing on a single toss to be 0.99. (We will leave out the details of how he is going to create the die in this text)

Since each toss is independent of the previous, he believes that he will almost ALWAYS get a “1” on each toss of the die. With this information, he created a new dice game. When the opponent throws a “1”, they will have to pay him $ 1. Otherwise, he is willing to pay the opponent a sum of money. He randomly selected the sum to be $ 120 in order to attract more players. He believes that even if he is SO damn unlucky to lose in one of the many tosses, he will still be able to make a profit in the long run. His explanation is as follows:

 

“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
per trial (N)

Number of final Winnings
that are Positive

Number of final Winnings
that are Negative

Total Number of
Trials

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

 

 


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