Deductive and Inductive Reasoning

How is logical reasoning used in developing theories?

Scientists use a combination of careful planning, creative thinking, and logical reasoning to come up with information and explanations for natural phenomena. While there are diverse elements in conducting a scientific inquiry, essential characteristics set science apart from other ways of describing and explaining natural phenomena.

Scientific methods are rigorous processes that involve making observations, defining problems, forming logical explanations in the form of hypotheses, testing these hypotheses through experiments, and drawing conclusions.

Scientists communicate these results to other members of the scientific community. When an explanation is tested and supported by other findings, it may become a theory. However, as more information is collected, theories can be revised.

Scientists use logical reasoning in carrying out scientific inquiries.

What is the definition of deductive and inductive reasoning?

There are two types of logical reasoning: deductive and inductive. Their definition is shown below.

Figure 1 below shows the fundamental difference in logical pattern between the two types.

What are some examples of deductive and inductive reasoning?

Let’s discuss examples of deductive and inductive reasoning.

For each type of logical reasoning, we will start with scenarios you might encounter in your everyday life. Then, we will discuss how these forms of logical reasoning are used in scientific inquiry.

Examples of Deductive Reasoning

Deductive reasoning begins with general premises from which we are to come up with a specific conclusion.

Let’s say I asked you if Bob is required to attend class today.

You might come up with a response this way:

• All students are required to attend class today.

• Bob is a student.

• Therefore, Bob is required to attend class today.

One way to think about deductive reasoning is by using an “if…then” statement. In Bob’s case: If all students are required to attend class today, and Bob is a student, then Bob has to attend class today.

Here’s an example you might encounter in biology:

• All living organisms are made up of Cells.

• All humans are living organisms.

• Therefore, all humans are made up of Cells.

In scientific inquiry, formulating and testing hypotheses typically involves deductive reasoning. Deductions are basically predictions of what will happen if a specific hypothesis is correct. When a hypothesis is tested, we will see whether or not the results are as expected.

For example, newly hatched ducks tend to make a bond with the first adult individual that they see. They will stay close to that adult, increasing their chances of survival. In the wild, this would typically be their mother.

We might ask: If a newly hatched duck sees an adult human first, will they make a bond with that human (Fig. 2)?

We can come up with the following deduction:

• All newly hatched ducks make a bond with the first adult they see and stay close to the adult.

• The first adult that a set of newly hatched ducks sees is Bob.

• Therefore, the newly hatched ducks will stay close to Bob.

We can then formulate the hypothesis as follows:

• If a set of newly hatched ducks see Bob, then they will stay close to Bob.

This hypothesis can be tested through a series of experiments. As strange as the hypothesis may sound, experiments have been conducted on this very topic. The results support the hypothesis: newly hatched ducklings stayed close to humans, provided that they made specific acoustic (a “kom kom kom” call) and visual (movement of the hand or the whole person away from the ducks) signals.

As mentioned earlier in the definition, a deduction will only hold true if the premises are correct. If the premises are incorrect, so will be the deductions even if the logical reasoning is valid. For this reason, deductive reasoning is more often applied in mathematics and physics, where the premises can be expressed as equations or axioms.

Consider the following:

• All squares have four sides.

• All triangles are squares.

• Therefore, triangles have four sides.

We know that the conclusion in this example is not logically sound. But why? While the reasoning is valid, the argument is based on a false premise: that all triangles are squares. By definition, triangles have three sides, and squares have four sides.

Of course, false premises are harder to identify in actual research.

In our previous example, for instance, the first premise that all newly hatched ducks bond with and follow the first adult they see was, in itself, a conclusion that researchers made after observing possibly thousands of ducks, a generalization extrapolated from observed cases. In short, the researchers assumed that this behavior holds true for all ducklings.

For this reason, complex sciences typically use deductive reasoning in combination with inductive reasoning, which we will go into in the next section.

Examples of inductive reasoning

Whereas the pattern of thinking in deductive reasoning is from general to specific, inductive reasoning entails reasoning from specific observations to reach a general conclusion.

Let’s say you want to avoid heavy traffic today. You noticed that in the past three months, the traffic tends to be heavy between 8AM to 10AM. You conclude that to avoid traffic, you have to drive earlier than 8AM or later than 10AM.

With inductive reasoning, conclusions are made from careful observations and analysis of relatively large amounts of data. It is important to note that the strength of inductive reasoning comes from the quantity and quality of supporting evidence.

For example, from your interaction with ten friendly dogs in your neighborhood, you cannot strongly argue that all dogs in the world are friendly.

Inductive reasoning is commonplace in descriptive science. For example, based on a series of rigorous experiments where all observed pieces of copper conducted electricity, researchers can strongly argue that all copper conducts electricity.

Darwin’s theory of evolution by Natural Selection is an example of how inductive reasoning can be used to explain complex phenomena. Rather than drawing from general principles, Darwin made a generalization from many specific pieces of evidence including:

• Comparing the anatomy of different organisms

• Field observations in the Galapagos Islands

• Observations of Selective Breeding

Darwin’s observations can be summarized as follows:

• There is Genetic Variation among individuals within a population.

• Individuals have to compete due to limited resources and other external factors.

• Individuals with favorable traits are more likely to survive and reproduce.

• In succeeding generations, more individuals will have these beneficial traits.

• As these traits accumulate, the population evolves.

From these observations, Darwin theorized that the differential ability of organisms to survive and reproduce leads to change in the genetic makeup of the population over time.

Complexities of the natural world make inductive reasoning necessary because there are phenomena that are difficult to deduce from “first principles” (or “correct principles”).

Inductive inferences are not drawn from a set number of logical steps (for example, A=B, B=C, therefore A=C); instead, they involve open-ended sets such as extrapolating past to future events (the traffic will be heavy from 8AM to 10AM) or observed to unobserved cases (the behavior of observed ducks must be the behavior of all ducks).

For this reason, inductive inferences cannot be proven to be true without a doubt, but they can be supported by experimental testing and reach scientific consensus; meaning, many scientists think that the hypothesis explains the known data well and stands up to experimental testing.

Difference between inductive and deductive reasoning

Let’s summarize the differences between deductive and inductive reasoning in the following table (Table 1):

Table 1. This table highlights the differences between deductive and inductive reasoning.

Similarities between inductive and deductive reasoning

While deductive reasoning tends to be used where premises can be expressed as equations and axioms, and inductive reasoning tends to be applied in descriptive sciences, the boundaries between the two are often blurred.

Many scientific endeavors combine both approaches. Researchers subject their hypotheses to a continuous process of testing and revising, as they come closer and closer to their best estimation of laws that govern natural phenomena.