Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions from the induced hypothesis "butterflies are attracted to specific flowers based on the petal color". These deductive tests are often formulated as "If…then" statements: if the hypothesis is true, then changing the flower's petal color should alter the butterfly's attraction, but changing its scent or its petal shape should not. Such predictions are used to set up experiments to test the hypothesis.
Although deductive reasoning is at the heart of hypothesis-driven science, and inductive reasoning is mostly associated with descriptive science, both forms of logic are integral to research and often tie together within the same experiments. Following the above example, the researcher might observe that butterflies also tend to avoid flowers with pointed petals. This observation can lead to a new inductive hypothesis, which can then be tested deductively.
Part of this text is adapted from Openstax, Biology 2e, Section 1.1: The Science of Biology
Reference:
Clark, M. A., Douglas, M., Choi, J. Section 1.1: The Science of Biology. In Biology 2e. OpenStax. Houston, TX (2018).
Deductive reasoning is a type of logic that uses general principles to make specific predictions or conclusions.
It is the opposite of inductive reasoning, where general principles are inferred from specific observations.
Both types of reasoning are used in the process of generating and testing hypotheses.
For example, a scientist observes that butterflies are attracted to red flowers, but not yellow ones.
Using inductive reasoning, they formulate the hypothesis that butterflies prefer specific flowers based on the color of their petals.
The scientist then employs deductive reasoning to predict a number of possible results and design experiments to test the hypothesis.
In this case, changing the flower's petal color should alter the butterfly's attraction, but changing its scent or its petal shape should not.
The results of the experiment may lead to further inductive hypotheses and deductive predictions. For instance, the scientist might observe that butterflies also tend to avoid flowers with pointed petals.
In this way, both inductive and deductive reasoning are used to help expand our scientific knowledge and understanding.
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