Uncertainty
Contents
Full Title or Meme
Context
Karl Pearson, the English statistician and geneticist, is commonly credited with first describing the concept of uncertainty as a measure of data variability in the late 1800s.[1] Before Pearson, scientists realized that their measurements incorporated variability, but they assumed that this variability was simply due to error. For example, measurement of the orbits of planets around the sun taken by different scientists at different times varied, and this variability was thought to be due to errors caused by inadequate instrumentation. The French mathematician Pierre-Simon Laplace discussed a method for quantifying error distributions of astronomical measurements caused by small errors associated with instrument shortcomings as early as 1820. As technology improved through the 1800s, astronomers realized that they could reduce, but not eliminate this error in their measurements.
Pearson put forward a revolutionary idea: Uncertainty, he proposed, was not simply due to the limits of technology in measuring certain events – it was inherent in nature. Even the most careful and rigorous scientific investigation (or any type of investigation for that matter) could not yield an exact measurement. Rather, repeating an investigation would yield a scatter of measurements that are distributed around some central value. This scatter would be caused not only by error, but also by natural variability. In other words, measurements themselves, independent of any human or instrument inaccuracies, exhibit scatter.
Whether it is the flight path of an arrow, the resting heart rate of an adult male, or the age of a historical artifact, measurements do not have exact values, but instead always exhibit a range of values, and that range can be quantified as uncertainty. This uncertainty can be expressed as a plot of the probability of obtaining a certain value, and the probabilities are distributed about some central, or mean, value.[2]
Based on the early papers of Quantum Mechanics before Heisenberg formulated his Uncertainty principle, JBS Haldane formulated his own "suspicion that the universe is not only queerer than we suppose, but queerer than we can suppose."[3]
Prediction
Most of science is an attempt to create as set of equations that will predict the future. It appears that knowing the future is an obsession with the human species. Whether it will rain, or where to find the next meal were important in the survival of the species and so has always consumed a great deal of the learning that humans pass onto their progeny. But we have know for as long as we have any records that this effort was troublesome. William Shakespeare has Hamlet state that human knowledge is limited: "There are more things in heaven and Earth, Horatio, / Than are dreamt of in your philosophy [science]."
Quantum Mechanics
Fourier Transforms
Uncertainty principles are not formally defined. In general, uncertainty principles refer to a meta-theorem in Fourier analysis that states that a nonzero function and its Fourier transform cannot be localized to arbitrary precision.[4]
More[5]
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References
- ↑ D. Salsburg, The lady tasting tea: How statistics revolutionized science in the twentieth century. New York: W. H. Freeman (2001) ISBN 9780805071344
- ↑ Anthony Carpi+1, Uncertainty, Error, and Confidence https://www.visionlearning.com/en/library/Process-of-Science/49/Uncertainty-Error-and-Confidence/157
- ↑ JBS Haldane, Possible Worlds (1927) https://jbshaldane.org/books/1927-Possible-Worlds/haldane-1927-possible-worlds.html#Page_260
- ↑ Kabir Dubey The Fourier uncertainty Principles University of Chicgo https://math.uchicago.edu/~may/REU2021/REUPapers/Dubey.pdf
- ↑ Emanuele Pesaresi, Uncertainty Principle Derivation from Fourier Analysis https://www.linkedin.com/pulse/uncertainty-principle-derivation-from-fourier-emanuele-pesaresi?utm_source=share&utm_medium=member_android&utm_campaign=share_via
- ↑ Jason Baker & Christian Roberts The Uncertainty Principle: Fourier Analysis In Quantum Mechanics (2016-11-20) https://math.unm.edu/~crisp/courses/wavelets/fall16/ChrisJasonUncertaintyPple.pdf
