What Is Deductive Reasoning? | Explanation & Examples

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning, where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic or top-down reasoning.

Deductive-reasoning

Note
Deductive reasoning is often confused with inductive reasoning. However, in inductive reasoning, you draw conclusions by going from the specific to the general.

What is deductive reasoning?

In deductive reasoning, you’ll often make an argument for a certain idea. You make an inference, or come to a conclusion, by applying different premises.

A premise is a generally accepted idea, fact, or rule, and it’s a statement that lays the groundwork for a theory or general idea. Conclusions are statements supported by premises.

Tip
Due to its reliance on inference, deductive reasoning is at high risk for research biases, particularly confirmation bias and other types of cognitive bias like belief bias. It can be tempting to seek out or prefer information that supports your inferences or ideas, but be careful about bias creeping into your research.

Deductive logic arguments

In a simple deductive logic argument, you’ll often begin with a premise, and add another premise. Then, you form a conclusion based on these two premises. This format is called “premise-premise-conclusion.”

Examples: Deductive logic arguments
Premise All insects have exactly six legs.
Premise Spiders have eight legs.
Conclusion Therefore, spiders are not insects.
Premise Blue litmus paper turns red in the presence of acid.
Premise The blue litmus paper turned red after I dropped some liquid on it.
Conclusion Therefore, the liquid is acidic.

Validity and soundness

Validity and soundness are two criteria for assessing deductive reasoning arguments.

Validity

In this context, validity is about the way the premises relate to each other and the conclusion. This is a different concept from research validity.

An argument is valid if the premises logically support and relate to the conclusion. But the premises don’t need to be true for an argument to be valid.

Examples: Valid (but untrue) deductive arguments
Example 1

  1. If there’s a rainbow, flights get canceled.
  2. There is a rainbow now.
  3. Therefore, flights are canceled.

Example 2

  1. All chili peppers are spicy.
  2. Tomatoes are a chili pepper.
  3. Therefore, tomatoes are spicy.

Both of these arguments are valid. Even though the premises are completely made up, they relate to each other in a way where you can justifiably infer the conclusion.

In an invalid argument, your premises can be true but that doesn’t guarantee a true conclusion. Your conclusion may inadvertently be true, but your argument can still be invalid because your conclusion doesn’t logically follow from the relationship between the statements.

Examples: Invalid deductive arguments
Example 1

  1. All leopards have spots.
  2. My pet gecko has spots.
  3. Therefore, my pet gecko is a leopard.

Example 2

  1. All US presidents live in the White House.
  2. Barack Obama lived in the White House.
  3. Therefore, Barack Obama was a US president.

Both of these are invalid because the truth of the premises doesn’t necessarily lead you to a true conclusion. You end up with a correct conclusion in the second example, but both arguments take the same invalid format.

Soundness

An argument is sound only if it’s valid and the premises are true. All invalid arguments are unsound.

If you begin with true premises and a valid argument, you’re bound to come to a true conclusion.

Examples: Sound deductive reasoning
Example 1

  1. Flights get canceled when there are extreme weather conditions.
  2. There are extreme weather conditions right now.
  3. Therefore, flights are canceled.

Example 2

  1. All fruits are grown from flowers and contain seeds.
  2. Tomatoes are grown from flowers and contain seeds.
  3. Therefore, tomatoes are fruits.

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Deductive reasoning in research

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research.

In research, you might have come across something called the hypothetico-deductive method. It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

This method is used for academic as well as non-academic research.

Example: Deductive research problem
You work as an organizational researcher at a large insurance organization. Currently, the organization is dealing with increasing levels of employee burnout, and you’re tasked with finding a solution to this problem.

Here are the general steps for deductive research:

  1. Select a research problem and create a problem statement.
  2. Develop falsifiable hypotheses.
  3. Collect your data with appropriate measures.
  4. Analyze and test your data.
  5. Decide whether to reject your null hypothesis.

Importantly, your hypotheses should be falsifiable. If they aren’t, you won’t be able to determine whether your results support them or not.

Example: Deductive research approach
You predict that going from a five-day work week to a four-day work week (without any reduction in pay) will help reduce or prevent burnout by improving employee well-being.

You formulate your main hypothesis: Switching to a four-day work week will improve employee well-being. Your null hypothesis states that there’ll be no difference in employee well-being before and after the change.

You collect data on employee well-being through quantitative surveys on a monthly basis before and after the change. When analyzing the data, you note a 25% increase in employee well-being after the change in work week.

Using a statistical test, you find that your results show statistical significance. You reject your null hypothesis and conclude that your results support your main hypothesis.

Deductive vs. inductive reasoning

Deductive reasoning is a top-down approach, while inductive reasoning is a bottom-up approach.

In deductive reasoning, you start with general ideas and work toward specific conclusions through inferences. Based on theories, you form a hypothesis. Using empirical observations, you test that hypothesis using inferential statistics and form a conclusion.

Inductive reasoning is also called a hypothesis-generating approach, because you start with specific observations and build toward a theory. It’s an exploratory method that’s often applied before deductive research.

In practice, most research projects involve both inductive and deductive methods.

Frequently asked questions about deductive reasoning

What is deductive reasoning?

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning, where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

How do you use deductive reasoning in research?

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research.

In research, you might have come across something called the hypothetico-deductive method. It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

What’s the difference between inductive and deductive reasoning?

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

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Pritha Bhandari

Pritha has an academic background in English, psychology and cognitive neuroscience. As an interdisciplinary researcher, she enjoys writing articles explaining tricky research concepts for students and academics.