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Residual sum of squares
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#	Item
31	Chapter 9 Simple Linear Regression An analysis appropriate for a quantitative outcome and a single quantitative explanatory variable. 9.1 Add to Reading List Source URL: www.stat.cmu.edu Language: English - Date: 2013-10-20 13:22:10 Simple linear regression Data transformation Least squares Residual sum of squares Errors and residuals in statistics Dummy variable Ordinary least squares Statistics Regression analysis Linear regression
32	COMPUTING PRESCRIPTIONS Editors: Isabel Beichl, [removed] FITTING NATURE’S BASIC FUNCTIONS PART I: POLYNOMIALS AND LINEAR LEAST SQUARES By Bert W. Rust Add to Reading List Source URL: math.nist.gov Language: English - Date: 2005-04-06 15:12:51 Normal distribution Least squares Ordinary least squares Linear regression Degrees of freedom Errors and residuals in statistics Residual sum of squares Non-linear least squares Heteroscedasticity-consistent standard errors Statistics Regression analysis Linear least squares
33	Fitting Equations Idea: The variable of interest (dependent variable, yi) is hard to measure. There are “easy to measure” variables (predictor/ independent) that are related to the variable of interest, labeled x1 Add to Reading List Source URL: biometrics.forestry.ubc.ca Language: English - Date: 2013-06-11 13:13:06 Least squares Linear regression Residual sum of squares Errors and residuals in statistics Coefficient of determination Dummy variable Linear least squares Degrees of freedom Variance Statistics Regression analysis Simple linear regression
34	PRESCRIPTIONS COMPUTING PRESCRIPTIONS Editors: Isabel Beichl, [removed] Julian V. Noble, [removed] Add to Reading List Source URL: math.nist.gov Language: English - Date: 2005-04-06 15:12:51 Non-linear least squares Nonlinear regression Linear least squares Least squares Nonlinear system Residual sum of squares Autoregressive conditional heteroskedasticity Dynamical system Regression analysis Statistics Sinusoidal model
35	Perturbation Bounds for Linear Regression Problems Bert W. Rust Computing and Applied Mathematics Division Building 101, Room A-238 National Institute of Standards and Technology Gaithersburg, MD 20899 Add to Reading List Source URL: math.nist.gov Language: English - Date: 2014-05-30 14:39:36 Econometrics Probability theory Numerical linear algebra Linear least squares Linear regression Residual sum of squares Condition number Expected value Normal distribution Statistics Regression analysis Least squares
36	Microsoft Word - Fitting Equations.doc Add to Reading List Source URL: biometrics.forestry.ubc.ca Language: English - Date: 2013-06-11 13:17:32 Estimation theory Econometrics Parametric statistics Residual sum of squares Errors and residuals in statistics Simple linear regression Linear regression Coefficient of determination Variance Statistics Regression analysis Least squares
37	Parameter Selection for Constrained Solutions to Ill-Posed Problems Bert W. Rust Reprinted from the CD Rust, B. W[removed]) “Parameter Selection for Constrained Solutions to Ill-Posed Problems,” Computing Science and S Add to Reading List Source URL: math.nist.gov Language: English - Date: 2005-04-06 15:12:38 Estimation theory Econometrics Measurement Linear least squares Residual sum of squares Errors and residuals in statistics Tikhonov regularization Degrees of freedom Periodogram Statistics Regression analysis Least squares
38	Package ‘leaps’ July 2, 2014 Title regression subset selection Version 2.9 Author Thomas Lumley using Fortran code by Alan Miller Description Regression subset selection including exhaustiv Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 12:17:09 Matrices Estimation theory Parametric statistics Linear regression Matrix Design matrix Residual sum of squares R Degrees of freedom Statistics Regression analysis Econometrics
39	Data-Based Models for Global Temperature Variations Bert W. Rust and Add to Reading List Source URL: math.nist.gov Language: English - Date: 2009-09-28 11:10:44 Coefficient of determination Linear regression Spline Residual sum of squares Errors and residuals in statistics Durbin–Watson statistic Smoothing spline Statistics Regression analysis Least squares
40	Microsoft Word - Fitting Equations.doc Add to Reading List Source URL: biometrics.forestry.ubc.ca Language: English - Date: 2013-06-11 13:13:08 Estimation theory Econometrics Parametric statistics Residual sum of squares Errors and residuals in statistics Simple linear regression Linear regression Coefficient of determination Variance Statistics Regression analysis Least squares

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