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2. 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. Numerical methods for linear least squares include inverting the ...

3. Linear regression - Wikipedia

   en.wikipedia.org/wiki/Linear_regression

   t. e. In statistics, linear regression is a statistical model which estimates the linear relationship between a scalar response (dependent variable) and one or more explanatory variables (regressor or independent variable). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple ...

4. Desmos - Wikipedia

   en.wikipedia.org/wiki/Desmos

   Desmos was founded by Eli Luberoff, a math and physics double major from Yale University, [3] and was launched as a startup at TechCrunch 's Disrupt New York conference in 2011. [4] As of September 2012, it had received around 1 million US dollars of funding from Kapor Capital, Learn Capital, Kindler Capital, Elm Street Ventures and Google ...

5. Simple linear regression - Wikipedia

   en.wikipedia.org/wiki/Simple_linear_regression

   Deming regression (total least squares) also finds a line that fits a set of two-dimensional sample points, but (unlike ordinary least squares, least absolute deviations, and median slope regression) it is not really an instance of simple linear regression, because it does not separate the coordinates into one dependent and one independent ...

6. Ordinary least squares - Wikipedia

   en.wikipedia.org/wiki/Ordinary_least_squares

   t. e. Okun's law in macroeconomics states that in an economy the GDP growth should depend linearly on the changes in the unemployment rate. Here the ordinary least squares method is used to construct the regression line describing this law. In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the ...

7. Theil–Sen estimator - Wikipedia

   en.wikipedia.org/wiki/Theil–Sen_estimator

   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. It has also been called Sen's slope estimator, [1][2] slope selection, [3][4] the single median method, [5] the ...

8. Linear trend estimation - Wikipedia

   en.wikipedia.org/wiki/Linear_trend_estimation

   Linear trend estimation is a statistical technique used to analyze data patterns. Data patterns, or trends, occur when the information gathered tends to increase or decrease over time or is influenced by changes in an external factor. Linear trend estimation essentially creates a straight line on a graph of data that models the general ...

9. Generalized least squares - Wikipedia

   en.wikipedia.org/wiki/Generalized_least_squares

   Regression analysis. In statistics, generalized least squares (GLS) is a method used to estimate the unknown parameters in a linear regression model. It is used when there is a non-zero amount of correlation between the residuals in the regression model. GLS is employed to improve statistical efficiency and reduce the risk of drawing erroneous ...