Inductive reasoning is a type of logical reasoning that involves drawing general conclusions from specific observations. It is the opposite of deductive reasoning, which involves drawing specific conclusions from general principles.
Inductive reasoning is often used in science, where scientists make observations and collect data to develop theories and hypotheses. For example, a scientist might observe that all swans they have ever seen are white. Based on this observation, they might conclude that all swans are white. This is an inductive conclusion, because it is based on a limited number of observations.
Inductive reasoning is also used in everyday life. For example, if you always get a wet umbrella when you go outside without checking the forecast, you might conclude that it is going to rain. This is an inductive conclusion, because it is based on your past experiences.
How Does Inductive Reasoning Work?
Inductive reasoning is based on the assumption that the future will be similar to the past. In other words, if we have observed something to be true in the past, we can assume that it will be true in the future.
Of course, this is not always the case. Just because all swans we have ever seen are white does not mean that all swans are white. There could be a black swan out there somewhere. However, inductive reasoning is still a useful tool for making predictions and decisions.
Types of Inductive Reasoning
There are two main types of inductive reasoning:
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Scott Crowe, Canva (Lead Recruiter - Data)