# 9: Inductive Reasoning - hypothetical, causal, statistical, and others

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Remember way back in Chapter One we introduced a distinction between deductive and inductive reasoning? Well, we’ve spent a lot of time on deductive reasoning, so we should spend at least a bit talking about inductive reasoning. Now, informal fallacies often have to do with inductive reasoning, and argument maps are a way of diagramming both inductive and deductive arguments, so we haven’t exactly skipped over inductive reasoning, but there are a few things to discuss that deal most specifically with a few different sorts of inductive arguments.

Scientists engage in a particular kind of reasoning to get from the evidence they collect to a theory about how the world works. This type of reasoning is “ampliative,” meaning the theory that the sun always rises in the morning in the East and sets in the evening in the West is based on seeing a relatively small number of sunrises and sunsets. Obviously, no one has seen all of the sunrises that ever happened. So how do we know? We add to the evidence by inferring conclusions that go beyond the evidence they have.

We everyday folks also engage in this kind of reasoning all the time. I get in my car, turn my car, it doesn’t start, and I begin to hypothesize what might be the cause. I notice that most of the men I talk to have deeper voices than most of the women I talk to and I (perhaps incorrectly?) infer that men tend to have deeper voices than women. I get cold, put my jacket on, and feel warmer. What do I infer? That the jacket keeps me warm.

What these everyday examples have in common with scientific reasoning is that they, too, are ampliative—the conclusions are stronger claims than the premises or evidence. If we couldn’t make inductive inferences, we’d be stuck in a strange situation. I’d see the sun rise and then learn…that the sun just rose. I wouldn’t learn anything over and above that particular fact. I might put my jacket on when I’m cold, get warmer, and learn…that I put my jacket on this one time and got warmer this one time. Not very exciting conclusions. We need induction to get conclusions that go beyond our evidence.

This chapter will cover a series of types of induction. First, we’ll cover Hypothetical Reasoning, which is the kind of reasoning that people call the “scientific method.” After that, we’ll cover the basics of Causal Reasoning, Statistical Generalization, and Arguing from Analogy. We’ll also explore the logic of each a bit and look at some pitfalls of each kind of reasoning.

This page titled 9: Inductive Reasoning - hypothetical, causal, statistical, and others is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by Andrew Lavin via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.