PROBABILISTIC ARGUMENT: CHARACTERISTICS AND EXAMPLES - CULTURE VOCABULARY - 2025

The probabilistic argument is a form of reasoning that uses possible or probable premises to obtain a conclusion. Therefore, this argument is based on logic and chance to establish possible events or phenomena.

For example: a coin has two sides, these being tails or heads. If we launch it, there is a 50% chance that it will land on heads. The same goes for dice; when thrown, there is a 50% chance that it will hit an odd number.

When rolling dice, there is a 50% chance that it will hit an odd number. Source: pixabay.com

The most probable arguments can be composed of qualitative or quantitative premises. In the first case, it is about premises that use words to designate a quantity. For example: half of the people present, most of the students, among others.

Instead, quantitative premises are those that use numbers to defend the argument. In many cases these numbers are accompanied by the% symbol. For example: 20% of students, 30% of animals, 2 out of 3 people, among others.

Origins of the probabilistic argument and other aspects

Probabilistic reasoning is very old. Its origins date back to Ancient Greece, where the most prominent speakers used the Eikóta to convince a certain audience. The word eikóta can be translated as "probable" or "credible" and was one of the arguments most used by the Greeks in judicial spaces.

The Eikota allowed Greek orators and thinkers to win many debates. For example, prominent speakers Corax and Tisias are known to have been highly sought after by people during political and judicial processes. These thinkers used probabilistic arguments effectively, allowing them to win countless cases and become famous.

Probability theory

It must be taken into account that the probabilistic arguments are based on the theory of probability. This consists of the scientific and mathematical study of random phenomena.

The objective of the theory is to assign a certain number to the possible results that arise in a random experiment, in order to quantify these results and to know if one phenomenon is more likely than another.

For example: if a person acquires a raffle ticket, where the total is 200 tickets, the probability that this person wins would be 1 in 200. As can be seen, the result has been quantified.

Probability theory was developed to solve certain problems that occurred in games of chance. Later, it began to be used in many other disciplines in order to know the operation of probability and logic in random events.

If we flip a coin, there is a 50% chance that it will land tails. Source: pixabay.com

Characteristics of the probabilistic argument

Combine logic with uncertainty

Probabilistic arguments are characterized by taking an event or phenomenon where there is a certain level of uncertainty to analyze it from logic.

For example: if a young person attends a job interview in which 50 people will attend, this young person has a 1% probability of obtaining the job and a 49% probability of not obtaining it. In this case, mathematical logic has been used to analyze an event where there is a degree of uncertainty (will the young person get the job?).

It is composed of probabilistic premises and conclusions

The probabilistic argument (like other types of arguments such as the abductive or inductive), is made up of one or more premises and a conclusion.

A premise consists of an informational statement that is intended to support or justify an event to reach a conclusion. On the other hand, the conclusion is a statement that has been born from the analysis of the premises.

For example:

Premise: Juan has a bag with three balls: two blue and the other purple.

Conclusion: if Juan draws one of the balls, there is a 66.6% chance that the ball that comes out will be blue, while there is a 33.3% chance that he will pull the purple ball.

It requires a mathematical calculation

In most cases, probabilistic arguments require a mathematical operation to be developed. This can be seen in the previous example, where it was necessary to calculate the numerical value of the purple ball and the blue balls.

It is a useful and applicable reasoning in everyday life

The probabilistic argument is used by many people around the world, sometimes even unconsciously. This happens because it is very practical knowledge that can help human beings understand and quantify their reality.

Consequently, probability arguments are not only applied by mathematicians and scientists; They are also used by students, teachers, merchants, among others.

For example: If a student studied half of the content that was on an exam, the student can make the following probabilistic argument:

Premise: I studied half of the content that was on the exam.

Conclusion: I have a 50% chance of passing the exam.

Examples of probabilistic arguments

The following probabilistic examples are presented below:

Example 1

Premise: In a dark bag, Patricia has 20 red apples and 10 green apples.

Conclusion: If Patricia extracts an apple from this bag, there is a 66.7% probability that she will extract a red apple. Instead, there is only a 33.3% chance that she will draw a green one.

Example 2

Premise: Carlos will roll the dice. You need to get a 6 to win.

Conclusion: The probabilities that Carlos wins are 1 in 6, since the dice has six faces and only one of them has the number 6.

Example 3

Premise: All living things die: animals, plants and humans.

Conclusion: The probability that living beings die is 100%, because death is inevitable.

Example 4

Premise: Ana María bought three raffles of 1000 numbers.

Conclusion: Ana María has a 3% probability of winning, while she has a 1997% probability of losing.

Example 5

Premise: Today 5 horses are competing in a race. Andrés bet on horse number 3.

Conclusion: The odds of horse 3 winning are 1 in 5, because there are five horses competing and Andrés bet on only one.

Horses competing. Source: pixabay.com

Themes of interest

Inductive argument.

Deductive argument.

Analog argument.

Conductive argument.

Argument from authority.

Abductive argument.

References

1. Alsina, A. (1980) Probabilistic language. Retrieved on March 12, 2020 from Scielo: scielo.br
2. Encyclopedia of Examples (2019) Probabilistic argument. Retrieved on March 12, 2020 from Examples.co
3. Haenni, R. (2009) Probabilistic argumentation. Retrieved on March 12, 2020 from Science Direct: sciencedirect.com
4. Hunter, A. (sf) Probabilistic argument graphs for argumentation lotteries. Retrieved on March 12, 2020 from cs.ucl.ac.uk
5. Leon, A. (sf) The 10 most prominent probabilistic argument examples. Retrieved on March 12, 2020 from Lifeder: lifeder.com
6. Mercado, H. (2014) The probability argument in Greek rhetoric. Retrieved on March 12, 2020 from Dialnet: Dialnet.net
7. Prakken, H. (2018) Probabilistic strength of arguments with structure. Retrieved on March 12, 2020 from cs.uu.nl
8. SA (sf) Probabilistic logic. Retrieved on March 12, 2020 from Wikipedia: es.wikipedia.org
9. SA (sf) Probability theory. Retrieved on March 12, 2020 from Wikipedia: es.wikipedia.com