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Popper, Bayes and the inverse problem

Using observations to infer the values of some parameters corresponds to solving an 'inverse problem'. Practitioners usually seek the 'best solution' implied by the data, but observations should only be used to falsify possible solutions, not to deduce any particular solution.

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Figure 1: Sideways.
Figure 2: Giant 'haystack'.

References

  1. Popper, K. The Logic of Scientific Discovery (Basic Books, 1959).

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  2. Stigler, M. S. The History of Statistics: The Measurement of Uncertainty Before 1900 (Belknap, Harvard, 1986).

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  4. Backus, G. Proc. Natl Acad. Sci. 65, 1–105 (1970); ibid. 65, 281–287 (1970); ibid. 67, 282–289 (1970).

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  6. Tarantola, A. Inverse Problem Theory and Methods for Model Parameter Estimation (SIAM, 2005).

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Tarantola, A. Popper, Bayes and the inverse problem. Nature Phys 2, 492–494 (2006). https://doi.org/10.1038/nphys375

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