What is Inductive Reasoning in Aristotelian Logic?

What is Inductive Reasoning in Aristotelian Logic?

June 26, 2021 Off By Felso

In his Analytics, Aristotle considered not only deductive scientific proof or demonstration, but also induction.

“Induction proceeds through a sequence of all cases and situations.” says. Then, induction works in the opposite direction, allowing one to reason from a specific situation or example such as “This swan is white” and arrive at a general conclusion such as “All swans are white”. Going from the particular to the general is just one of the ways inductive arguments differ from deductive ones. The two also differ in that deduction is certain, whereas induction is probable. However, Aristotle’s ideal reasoning is deductive, in other words, syllogistic notation.

Intermediate Note: Aristotle’s Opposition Square, which is a diagram examining the relations between propositions, is one of the most useful educational tools for anyone trying to develop any thesis, attack a freshman or defend a thesis. One might argue that “All stealing is bad”. But the square reminds us that all we need to defeat such a universal positive thesis is one example: “Some thefts are not bad.”

However, few arguments in everyday life are deductive. Sometimes when trying to prove a number, one’s best is to arrive at probable conclusions. So, you can reason like this: “Every time I set my watch for 6 am, my watch went off at 6 am. So the next time I set my watch for 6 am, it will ring at 6 am.” Of course, it may be true that your clock will ring once again at 6 a.m. and you hope it does. The probability of it ringing is high, in other words, the probability is close to one, that is, it is close to certainty. (In knowable probability, the probability is a number between zero and one. At zero probability, the event does not occur. At 1, the event will definitely occur. At 0.5, the probability of the event occurring is half.) However, you cannot be sure that it will ring; this is a possibility.

Inductive arguments, then, are those in which subsequent inferences are probabilistic. Many of the implications from your daily life are similarly probabilistic. You expect the drive from home to work to take thirty minutes, because it usually takes thirty minutes. In addition, because your car was in good condition yesterday and the day before, you expect it to run flawlessly today and tomorrow. The thing to note here is that your 30-minute commute depends on many probabilistic factors, again: traffic, weather, condition of your car, accidents on the road, and so on. You can calculate the probability of getting to work in thirty minutes by multiplying the probability of each of these events.

Intermediate Note: Is it possible for things based on experience to be certain? It’s tempting to think so. For example, the sun has always risen, so you might conclude that it will rise tomorrow. Similarly, penicillin has always relieved your sore throat in the past, so you infer that it will be useful next time as well. But both inferences are only probable; so the probability is less than one.

Probabilities often play a role in sports. If you have seen a football player, let’s say, Fenerbahce Alex scored 25 goals every season in the past years, you can expect him to score 25 goals this year as well. In this type of reasoning, your conclusions are based on evidence with a certain degree of probability (probability that sits somewhere between 0 and 1 on the spectrum) and is therefore inductive. One of the characteristics of such inductive arguments is that you expect the future to be similar to the past.

Prepared by: Sociologist Ömer YILDIRIM
Source: Omer YILDIRIM’s Personal Lecture Notes. Atatürk University Sociology Department 1st Year “Introduction to Philosophy” and 2nd, 3rd, 4th Grade “History of Philosophy” Lecture Notes (Ömer YILDIRIM); Open Education Philosophy Textbook