Text: Inductive and Deductive Reasoning

Two Ways of Understanding

We have two basic approaches for how we come to believe something is true.

The first way is that we are exposed to several different examples of a situation, and from those examples, we conclude a general truth. For instance, you visit your local grocery store daily to pick up necessary items. You notice that on Friday, two weeks ago, all the clerks in the store were wearing football jerseys. Again, last Friday, the clerks wore their football jerseys. Today, also a Friday, they’re wearing them again. From just these observations, you can conclude that on all Fridays, these supermarket employees will wear football jerseys to support their local team.

This type of pattern recognition, leading to a conclusion, is known as inductive reasoning.

Knowledge can also move the opposite direction. Say that you read in the news about a tradition in a local grocery store, where employees wore football jerseys on Fridays to support the home team. This time, you’re starting from the overall rule, and you would expect individual evidence to support this rule. Each time you visited the store on a Friday, you would expect the employees to wear jerseys.

Such a case, of starting with the overall statement and then identifying examples that support it, is known as deductive reasoning.

Two boxes: General Principle on left, Special Case on right. An arrow above moves from left to right, labeled deductive reasoning. An arrow below moves from right to left, labeled inductive reasoning.

The Power of Inductive Reasoning

You have been employing inductive reasoning for a very long time. Inductive reasoning is based on your ability to recognize meaningful patterns and connections. By taking into account both examples and your understanding of how the world works, induction allows you to conclude that something is likely to be true. By using induction, you move from specific data to a generalization that tries to capture what the data “mean.”

Imagine that you ate a dish of strawberries and soon afterward your lips swelled. Now imagine that a few weeks later you ate strawberries and soon afterwards your lips again became swollen. The following month, you ate yet another dish of strawberries, and you had the same reaction as formerly. You are aware that swollen lips can be a sign of an allergy to strawberries. Using induction, you conclude that, more likely than not, you are allergic to strawberries.

Data: After I ate strawberries, my lips swelled (1st time).

Data: After I ate strawberries, my lips swelled (2nd time).

Data: After I ate strawberries, my lips swelled (3rd time).

Additional Information: Swollen lips after eating strawberries may be a sign of an allergy.

Conclusion: Likely I am allergic to strawberries.

Inductive reasoning can never lead to absolute certainty. Instead, induction allows you to say that, given the examples provided for support, the claim more likely than not is true. Because of the limitations of inductive reasoning, a conclusion will be more credible if multiple lines of reasoning are presented in its support.

The results of inductive thinking can be skewed if relevant data are overlooked. In the previous example, inductive reasoning was used to conclude that I am likely allergic to strawberries after suffering multiple instances of my lips swelling. Would I be as confident in my conclusion if I were eating strawberry shortcake on each of those occasions? Is it reasonable to assume that the allergic reaction might be due to another ingredient besides strawberries?

This example illustrates that inductive reasoning must be used with care. When evaluating an inductive argument, consider

  • the amount of the data,
  • the quality of the data,
  • the existence of additional data,
  • the relevance of necessary additional information, and
  • the existence of additional possible explanations.

Inductive Reasoning Put to Work

A synopsis of the features, benefits, and drawbacks of inductive reasoning can be found in this video.



The Power of Deductive Reasoning

Deductive reasoning is built on two statements whose logical relationship should lead to a third statement that is an unquestionably correct conclusion, as in the following example.

All raccoons are omnivores.
This animal is a raccoon.
This animal is an omnivore.

If the first statement is true (All raccoons are omnivores) and the second statement is true (This animal is a raccoon), then the conclusion (This animal is an omnivore) is unavoidable. If a group must have a certain quality, and an individual is a member of that group, then the individual must have that quality.

Going back to the example from the opening of this page, we could frame it this way:

Grocery store employees wear football jerseys on Fridays.
Today is Friday.
Grocery store employees will be wearing football jerseys today.

Unlike inductive reasoning, deductive reasoning allows for certainty as long as certain rules are followed.

Evaluating the Truth of a Premise

A formal argument may be set up so that, on its face, it looks logical. However, no matter how well-constructed the argument is, the additional information required must be true. Otherwise any inferences based on that additional information will be invalid. 

Inductive reasoning can often be hidden inside a deductive argument. That is, a generalization reached through inductive reasoning can be turned around and used as a starting “truth” a deductive argument. For instance, 

Most Labrador retrievers are friendly.
Kimber is a Labrador retriever.
Therefore, Kimber is friendly.

In this case we cannot know for certain that Kimber is a friendly Labrador retriever. The structure of the argument may look logical, but it is based on observations and generalizations rather than indisputable facts.

Methods to Evaluate the Truth of a Premise

One way to test the accuracy of a premise is to apply the same questions asked of inductive arguments. As a recap, you should consider

  • the amount of the data,
  • the quality of the data,
  • the existence of additional data,
  • the relevance of the additional data, and
  • the existence of additional possible explanations.

Determine whether the starting claim is based upon a sample that is both representative and sufficiently large, and ask yourself whether all relevant factors have been taken into account in the analysis of data that leads to a generalization.

Another way to evaluate a premise is to determine whether its source is credible.

  • Are the authors identified?
  • What is their background?
  • Was the claim something you found on an undocumented website?
  • Did you find it in a popular publication or a scholarly one?
  • How complete, how recent, and how relevant were the studies or statistics discussed in the source?

Overview and Recap

A synopsis of the features, benefits, and drawbacks of deductive reasoning can be found in this video.