Purnima Lallan Sharma Foundation · Est. 2021
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Knowledge, inference and scientific explanation

Develop an argument from its evidence, study classical Nyāya and test the assumptions behind scientific explanations.

3 lessons · Learn at your own pace

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Stacks of books, wooden catalogue drawers and bookshelves inside the State Central Library in Hyderabad.
State Central Library, Hyderabad; photographed in December 2024. · Saiphani02 · CC BY 4.0

Learn, practise, explain

Try the exercise before reading its explanation. Answer the self-check questions in your own words, then compare your reasoning with the answers. Revisit any difficult section before moving on. No account or payment is needed.

  1. 01

    Knowledge, belief and evidence

    You can believe a bus leaves at nine, correctly guess that it leaves at nine, or know its departure time from a reliable current timetable. The answer may look identical while the route to it differs. This lesson builds on the distinction between claims, reasons and valid inference.

    Learning outcome: Distinguish truth, belief and justification; compare perception, inference and testimony; and explain why appropriate confidence may change with new evidence.

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  2. 02

    Nyāya: means of knowledge and testing inference

    How can a reason carry us beyond what we immediately see? Classical Nyāya offers an exacting account of knowledge, inference and discussion. Its concepts help us examine arguments, but belong to a larger philosophical project concerning error, suffering and liberation.

    Learning outcome: Identify the parts of an inference, reconstruct a five-member demonstration, and locate the precise point where an attractive argument fails.

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  3. 03

    Philosophy of science: models, explanation and testing

    A model can predict accurately without telling us every cause, and a failed prediction does not identify its own source of failure. Philosophy of science examines these distinctions. We use invented examples to connect explanation, idealisation, falsifiability and responsible revision.

    Learning outcome: Identify what a model represents, reconstruct the logic of a test, and explain when revising an assumption is informative rather than an excuse to avoid evidence.

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