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1.4: Inductive Reasoning

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Inductive Reasoning

1.4: Inductive Reasoning

Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.

Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or quantitative, and one can supplement the raw data with drawings, pictures, photos, or videos. From many observations, the scientist can infer conclusions based on evidence.

For example, a scientist observes that many butterflies visit red colored flowers but not yellow flowers in the same garden. The scientist can then make an inductive conclusion from this observation that butterflies are attracted to red colored flowers. This conclusion can then be used to formulate a testable, falsifiable hypothesis — that butterflies are only attracted to red flowers. In order to test this hypothesis, the scientist might set up an experiment with flowers of different petal colors and observe how the butterflies behave. The results may lead to the conclusion that butterflies are attracted to both pink and red flowers, and not just red flowers.

Part of this text is adapted from Openstax, Biology 2e, Section 1.1: The Science of Biology

Suggested Reading


Inductive Reasoning Logic Generalizations Specific Observations Conclusion Testable Hypothesis Falsifiable Hypothesis Logical Thinking Related Observations Uncertain Degrees Of Credibility Weak Argument Strong Argument Descriptive Science Life Scientist Qualitative Data Quantitative Data Evidence

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