This article examines how inductive generalization serves as a method to infer pandemic case numbers and lethality from sample data. It explains the philosophical distinctions between inductive and deductive reasoning, emphasizing that inductive arguments provide support for conclusions but do not guarantee their truth. The concept of the inductive leap, which involves concluding based on observed evidence, is discussed alongside David Hume's contributions, revealing the inherent uncertainties and limitations of inductive reasoning in the context of public health data during a pandemic.
Inductive reasoning allows for conclusions to be derived from observed data, yet these conclusions may extend beyond the observed premises, raising questions about certainty and validity.
The inductive leap highlights the inherent uncertainty of inductive reasoning—strong arguments can present true premises but still reach an incorrect conclusion.
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