What is inductive reasoning in your own words?

Even if we’re not conscious of it, we use inductive reasoning everyday. But what is inductive reasoning? We’re going to answer that question by looking at inductive reasoning examples from history. We’ll also show you how to recognize it in everyday life. By the end, you’ll know how to apply inductive logic and reasoning in the real world.

Inductive Reasoning is a “bottom-up” process of making generalized assumptions based on specific premises. Inductions are usually made at a subconscious level, but they play an integral role in our actions and beliefs. For example, an induction could state that everybody at a party was wearing blue shirts, Laura was at the party, therefore she was wearing a blue shirt. 

• Bottom-to-Top reasoning
• Effective for World Building
• Predictive, not Certain

What is inductive reasoning? What is the difference between inductive reasoning and deductive reasoning? Well, as I alluded to earlier, inductive reasoning applies a “bottom to top” approach to logic, while deductive reasoning applies a “top to bottom” approach. 

With deductive reasoning, if the premises of a statement are true, then the conclusion has to be true. But with the inductive form, even if the premises are true, that doesn’t mean the conclusion has to be true.

There’s also a third branch of reasoning called abductive reasoning. Abductive reasoning takes a conclusion, and hypothesizes the likeliest premises given the situation. This next video does a great job of explaining these three branches of reasoning, with special emphasis on inductive and abductive reasoning.

It may be helpful to think of inductive and abductive reasoning as forms of predictive logic — or “not-for-sure” logic. With deductive reasoning, the conclusion is assured by the premises, even if they’re ultimately proven false. But with inductive and abductive reasoning, there’s no certain answer, just educated guesses.

Inductive vs Deductive Reasoning Meaning

What does inductive reasoning mean?

The inductive reasoning meaning lies somewhere between a predictive inference and a scientific guess. Inductions can be made in three ways:

• A priori - (pure reason, practical reason)

Philosopher Immanuel Kant argued that pure reason, such as the statement “all bachelors are unmarried,” could be used to make deductions. But when the clauses of a statement are uncertain, we call that model practical reason.

An example of a practically reasonable induction would be: star SN87 went supernova, the sun is a star, therefore it will go supernova.

• A posteriori - (personal knowledge)

An example of an a posteriori induction is Plato’s Allegory of the Cave — it takes the lived experience of a man, uses his specific, empirically induced perception of the world, and reaches a generalized conclusion.

If you’re still racking your brain over these terms, don’t worry, this next video explains them in a short and succinct way.

• Combination of both (analytic and synthetic)

An analytic and synthetic example would take a universal predictive model and combine it with lived experience. For example: I sold a PlayStation 4 for $200, it’s been one year since then, so I assume I won’t be able to sell another PlayStation for the same value.

Inductive Reasoning Meaning

Types of inductive reasoning

There are a lot of different types of inductive reasoning. But before we go over these types in detail, check out the video below.

Take a specific observation and make a generalized conclusion. Example: “Every bear I’ve seen had black fur. Therefore, most bears probably have black fur.”

2. Statistical 

Statistical inductions take data into account to give a more accurate prediction. Example: “Eight of the ten bears I’ve seen in the wild had black fur. So, about 80% of the world’s bears have black fur.”

3. Bayesian

Bayesian inferences add circumstantial information to statistical data. Example: “I’ve only ever seen bears on the west coast of the United States, so my data may not accurately reflect the whole world.

4. Syllogism 

This is when you take a generalization about a group and apply it to an individual. Example: “All the bears at the zoo have had black fur, so the next bear they bring in will have black fur too.”

5. Analogical 

Comparing two things with a shared quality and inducing that they must have another shared quality too. Example: “Black bears have black fur. Black panthers have black fur. Therefore, black bears and black panthers are the same species.

6. Causal Inference 

When you infer a correlation between two causal events. Example: “I only see black bears when it gets hot outside. I suspect I’ll see a black bear this week during the heat-wave.”