A probabilistic argument is one that starts from at least one of its premises as probable or possible to reach a conclusion.
Probabilistic arguments take into account the circumstances and the action of chance, logic and the possibility of something happening.
Use of probabilistic arguments
These arguments are used in empirical science, which requires experience to extract the possibility of recurrence.
Types of probabilistic arguments
There are two ways to recognize an argument of these characteristics:
- Quantitative probabilistic argument . Use percentages or numbers to extract the argument. For example: One in three women are employed in Argentina. / 75% of the body is made up of water.
- Qualitative probabilistic argument . The argument does not use percentages but uses adverbs of quantity . For example: The half of these passed the exam more than 8. / The majority of employees complained about the action taken by the company.
Examples of probabilistic argument
- When tossing a coin, we have a 50% chance that it will land tails.
- It has not stopped raining for days and, according to the weather service, there is a 90% probability that it will also rain today.
- When I roll a die, I have a 50% chance that an even number will roll.
- In a Spanish card game, if I wish to draw a spade card, I have a 25% chance .
- The minority of the guests stayed to clean up after the party.
- If I have one black and two white marbles in a bag, I have a 66.6% probability that one of the white marbles will come out, while I only have a 33.3% chance of extracting the black canine.
- If I play a race with three of my friends, (we would be four in total) I have a 25% chance of winning and a 75% chance of not winning .
- If I apply for a job with 100 candidates, I have a 1% chance of getting that position and a 99% chance of not getting it.
- In a horse race, if there are five of them competing but I want No. 4 to win, I have a 20% chance that this one will win and an 80% chance that he will not win.
- If I study, I have a high probability of passing next week’s exam
