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  2. MedCalc - Wikipedia

    en.wikipedia.org/wiki/MedCalc

    [2] [3] [4] It has an integrated spreadsheet for data input and can import files in several formats (Excel, SPSS, CSV, ...). MedCalc includes basic parametric and non-parametric statistical procedures and graphs such as descriptive statistics , ANOVA , Mann–Whitney test , Wilcoxon test , χ 2 test , correlation , linear as well as non-linear ...

  3. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    Simple linear regression and multiple regression using least squares can be done in some spreadsheet applications and on some calculators. While many statistical software packages can perform various types of nonparametric and robust regression, these methods are less standardized.

  4. Polynomial regression - Wikipedia

    en.wikipedia.org/wiki/Polynomial_regression

    Although polynomial regression is technically a special case of multiple linear regression, the interpretation of a fitted polynomial regression model requires a somewhat different perspective. It is often difficult to interpret the individual coefficients in a polynomial regression fit, since the underlying monomials can be highly correlated.

  5. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    A model with exactly one explanatory variable is a simple linear regression; a model with two or more explanatory variables is a multiple linear regression. [1] This term is distinct from multivariate linear regression , which predicts multiple correlated dependent variables rather than a single dependent variable.

  6. Multivariate probit model - Wikipedia

    en.wikipedia.org/wiki/Multivariate_probit_model

    In statistics and econometrics, the multivariate probit model is a generalization of the probit model used to estimate several correlated binary outcomes jointly. For example, if it is believed that the decisions of sending at least one child to public school and that of voting in favor of a school budget are correlated (both decisions are binary), then the multivariate probit model would be ...

  7. Residual sum of squares - Wikipedia

    en.wikipedia.org/wiki/Residual_sum_of_squares

    The general regression model with n observations and k explanators, the first of which is a constant unit vector whose coefficient is the regression intercept, is = + where y is an n × 1 vector of dependent variable observations, each column of the n × k matrix X is a vector of observations on one of the k explanators, is a k × 1 vector of true coefficients, and e is an n× 1 vector of the ...

  8. Generalized least squares - Wikipedia

    en.wikipedia.org/wiki/Generalized_least_squares

    The model is estimated by OLS or another consistent (but inefficient) estimator, and the residuals are used to build a consistent estimator of the errors covariance matrix (to do so, one often needs to examine the model adding additional constraints; for example, if the errors follow a time series process, a statistician generally needs some ...

  9. Comparison of statistical packages - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_statistical...

    "A Short Preview of Free Statistical Software Packages for Teaching Statistics to Industrial Technology Majors" (PDF). Journal of Industrial Technology. 21 (2). Archived from the original (PDF) on October 25, 2005.