enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    Graph of points and linear least squares lines in the simple linear regression numerical example The 0.975 quantile of Student's t -distribution with 13 degrees of freedom is t * 13 = 2.1604 , and thus the 95% confidence intervals for α and β are

  3. 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.

  4. 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.

  5. Least squares - Wikipedia

    en.wikipedia.org/wiki/Least_squares

    The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. In regression analysis, least squares is a parameter estimation method based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each ...

  6. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems involved in linear regression, including variants for ordinary (unweighted), weighted, and generalized (correlated) residuals.

  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 ...

  8. Theil–Sen estimator - Wikipedia

    en.wikipedia.org/wiki/Theil–Sen_estimator

    The dashed green line represents the ground truth from which the samples were generated. In non-parametric statistics, the Theil–Sen estimator is a method for robustly fitting a line to sample points in the plane (simple linear regression) by choosing the median of the slopes of all lines through pairs of points.

  9. Least trimmed squares - Wikipedia

    en.wikipedia.org/wiki/Least_trimmed_squares

    "An algorithm for computing exact least-trimmed squares estimate of simple linear regression with constraints". Computational Statistics & Data Analysis . 48 (4): 717– 734.