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  2. Quantile function - Wikipedia

    en.wikipedia.org/wiki/Quantile_function

    The quantile function, Q, of a probability distribution is the inverse of its cumulative distribution function F. The derivative of the quantile function, namely the quantile density function, is yet another way of prescribing a probability distribution. It is the reciprocal of the pdf composed with the quantile function.

  3. Volcano plot (statistics) - Wikipedia

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

    Volcano plot showing metabolomic data. The red arrows indicate points-of-interest that display both large magnitude fold-changes (x axis) and high statistical significance (-log 10 of p value, y axis).

  4. Partial least squares regression - Wikipedia

    en.wikipedia.org/wiki/Partial_least_squares...

    Partial least squares (PLS) regression is a statistical method that bears some relation to principal components regression and is a reduced rank regression [1]; instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space of maximum ...

  5. Computational biology - Wikipedia

    en.wikipedia.org/wiki/Computational_biology

    Understanding how individual genes contribute to the biology of an organism at the molecular, cellular, and organism levels is known as gene ontology. The Gene Ontology Consortium 's mission is to develop an up-to-date, comprehensive, computational model of biological systems , from the molecular level to larger pathways, cellular, and organism ...

  6. Explained variation - Wikipedia

    en.wikipedia.org/wiki/Explained_variation

    In statistics, explained variation measures the proportion to which a mathematical model accounts for the variation of a given data set. Often, variation is quantified as variance ; then, the more specific term explained variance can be used.

  7. Proportional hazards model - Wikipedia

    en.wikipedia.org/wiki/Proportional_hazards_model

    Using this score function and Hessian matrix, the partial likelihood can be maximized using the Newton-Raphson algorithm. The inverse of the Hessian matrix, evaluated at the estimate of β , can be used as an approximate variance-covariance matrix for the estimate, and used to produce approximate standard errors for the regression coefficients.