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  2. Least-squares adjustment - Wikipedia

    en.wikipedia.org/wiki/Least-squares_adjustment

    There are three forms of least squares adjustment: parametric, conditional, and combined: In parametric adjustment, one can find an observation equation h(X) = Y relating observations Y explicitly in terms of parameters X (leading to the A-model below).

  3. Observational error - Wikipedia

    en.wikipedia.org/wiki/Observational_error

    Systematic errors can be either constant, or related (e.g. proportional or a percentage) to the actual value of the measured quantity, or even to the value of a different quantity (the reading of a ruler can be affected by environmental temperature). When it is constant, it is simply due to incorrect zeroing of the instrument.

  4. Expectation value (quantum mechanics) - Wikipedia

    en.wikipedia.org/wiki/Expectation_value_(quantum...

    In quantum mechanics, the expectation value is the probabilistic expected value of the result (measurement) of an experiment. It can be thought of as an average of all the possible outcomes of a measurement as weighted by their likelihood, and as such it is not the most probable value of a measurement; indeed the expectation value may have zero probability of occurring (e.g. measurements which ...

  5. Maximum likelihood estimation - Wikipedia

    en.wikipedia.org/wiki/Maximum_likelihood_estimation

    The expected value of the number m on the drawn ticket, and therefore the expected value of ^, is (n + 1)/2. As a result, with a sample size of 1, the maximum likelihood estimator for n will systematically underestimate n by ( n − 1)/2.

  6. Tienstra formula - Wikipedia

    en.wikipedia.org/wiki/Tienstra_formula

    J. M. Tienstra [] (1895-1951) was a professor of the Delft university of Technology where he taught the use of barycentric coordinates in solving the resection problem. It seems most probable that his name became attached to the procedure for this reason, though when, and by whom, the formula was first proposed is unknown.

  7. Probable error - Wikipedia

    en.wikipedia.org/wiki/Probable_error

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  9. Most probable number - Wikipedia

    en.wikipedia.org/wiki/Most_probable_number

    The most probable number method, otherwise known as the method of Poisson zeroes, is a method of getting quantitative data on concentrations of discrete items from positive/negative (incidence) data. Purpose