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  2. Mode (statistics) - Wikipedia

    en.wikipedia.org/wiki/Mode_(statistics)

    The mode of a sample is the element that occurs most often in the collection. For example, the mode of the sample [1, 3, 6, 6, 6, 6, 7, 7, 12, 12, 17] is 6. Given the list of data [1, 1, 2, 4, 4] its mode is not unique. A dataset, in such a case, is said to be bimodal, while a set with more than two modes may be described as multimodal.

  3. Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Excel

    Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS.It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA).

  4. Unimodality - Wikipedia

    en.wikipedia.org/wiki/Unimodality

    The term "mode" in this context refers to any peak of the distribution, not just to the strict definition of mode which is usual in statistics. If there is a single mode, the distribution function is called "unimodal". If it has more modes it is "bimodal" (2), "trimodal" (3), etc., or in general, "multimodal". [2]

  5. Failure mode, effects, and criticality analysis - Wikipedia

    en.wikipedia.org/wiki/Failure_Mode,_Effects,_and...

    The failure mode may then be charted on a criticality matrix using severity code as one axis and probability level code as the other. For quantitative assessment, modal criticality number C m {\displaystyle C_{m}} is calculated for each failure mode of each item, and item criticality number C r {\displaystyle C_{r}} is calculated for each item.

  6. Mean shift - Wikipedia

    en.wikipedia.org/wiki/Mean_shift

    where are the input samples and () is the kernel function (or Parzen window). is the only parameter in the algorithm and is called the bandwidth. This approach is known as kernel density estimation or the Parzen window technique. Once we have computed () from the equation above, we can find its local maxima using gradient ascent or some other optimization technique. The problem with this ...

  7. Ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Ordinary_least_squares

    In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model (with fixed level-one [clarification needed] effects of a linear function of a set of explanatory variables) by the principle of least squares: minimizing the sum of the squares of the differences between the observed dependent variable (values ...

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  9. Modal analysis - Wikipedia

    en.wikipedia.org/wiki/Modal_analysis

    Once a set of modes has been calculated for a system, the response to any kind of excitation can be calculated as a superposition of modes. This means that the response is the sum of the different mode shapes each one vibrating at its frequency. The weighting coefficients of this sum depend on the initial conditions and on the input signal.

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