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  2. Outline of regression analysis - Wikipedia

    en.wikipedia.org/wiki/Outline_of_regression_analysis

    Regression analysis – use of statistical techniques for learning about the relationship between one or more dependent variables (Y) and one or more independent variables (X). Overview articles [ edit ]

  3. Design matrix - Wikipedia

    en.wikipedia.org/wiki/Design_matrix

    A regression model may be represented via matrix multiplication as y = X β + e , {\displaystyle y=X\beta +e,} where X is the design matrix, β {\displaystyle \beta } is a vector of the model's coefficients (one for each variable), e {\displaystyle e} is a vector of random errors with mean zero, and y is the vector of predicted outputs for each ...

  4. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the outcome or response variable, or a label in machine learning parlance) and one or more error-free independent variables (often called regressors, predictors, covariates, explanatory ...

  5. Autoregressive model - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_model

    The autoregressive model specifies that the output variable depends linearly on its own previous values and on a stochastic term (an imperfectly predictable term); thus the model is in the form of a stochastic difference equation (or recurrence relation) which should not be confused with a differential equation.

  6. Contingency table - Wikipedia

    en.wikipedia.org/wiki/Contingency_table

    The example above is the simplest kind of contingency table, a table in which each variable has only two levels; this is called a 2 × 2 contingency table. In principle, any number of rows and columns may be used. There may also be more than two variables, but higher order contingency tables are difficult to represent visually.

  7. Random forest - Wikipedia

    en.wikipedia.org/wiki/Random_forest

    Random forests or random decision forests is an ensemble learning method for classification, regression and other tasks that works by creating a multitude of decision trees during training. For classification tasks, the output of the random forest is the class selected by most trees.

  8. Run chart - Wikipedia

    en.wikipedia.org/wiki/Run_chart

    A simple run chart showing data collected over time. The median of the observed data (73) is also shown on the chart. A run chart, also known as a run-sequence plot is a graph that displays observed data in a time sequence.

  9. NCSS (statistical software) - Wikipedia

    en.wikipedia.org/wiki/NCSS_(statistical_software)

    NCSS is a statistics package produced and distributed by NCSS, LLC. Created in 1981 by Jerry L. Hintze, NCSS, LLC specializes in providing statistical analysis software to researchers, businesses, and academic institutions.