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  2. Altman Z-score - Wikipedia

    en.wikipedia.org/wiki/Altman_Z-score

    Example of an Excel spreadsheet that uses Altman Z-score to predict the probability that a firm will go into bankruptcy within two years . The Z-score formula for predicting bankruptcy was published in 1968 by Edward I. Altman, who was, at the time, an Assistant Professor of Finance at New York University.

  3. Mode (statistics) - Wikipedia

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

    In statistics, the mode is the value that appears most often in a set of data values. [1] If X is a discrete random variable, the mode is the value x at which the probability mass function takes its maximum value (i.e., x=argmax x i P(X = x i)). In other words, it is the value that is most likely to be sampled.

  4. Circular error probable - Wikipedia

    en.wikipedia.org/wiki/Circular_error_probable

    The Spall and Maryak approach applies when the shot data represent a mixture of different projectile characteristics (e.g., shots from multiple munitions types or from multiple locations directed at one target).

  5. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    Sometimes we can remove the nuisance parameters by considering a likelihood based on only part of the information in the data, for example by using the set of ranks rather than the numerical values. Another example occurs in linear mixed models , where considering a likelihood for the residuals only after fitting the fixed effects leads to ...

  6. Prediction interval - Wikipedia

    en.wikipedia.org/wiki/Prediction_interval

    Given a sample from a normal distribution, whose parameters are unknown, it is possible to give prediction intervals in the frequentist sense, i.e., an interval [a, b] based on statistics of the sample such that on repeated experiments, X n+1 falls in the interval the desired percentage of the time; one may call these "predictive confidence intervals".

  7. Conditional probability table - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability_table

    The first column sum is the probability that x =0 and y equals any of the values it can have – that is, the column sum 6/9 is the marginal probability that x=0. If we want to find the probability that y=0 given that x=0, we compute the fraction of the probabilities in the x=0 column that have the value y=0, which is 4/9 ÷

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