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Regression, ANOVA, and the General Linear Model: A Statistics Primer

The author demonstrates basic statistical concepts from two different perspectives, giving the reader a conceptual understanding of how to;

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A Primer on Linear Models

of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then;

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A Primer on Linear Models

of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then;

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Foundations of Behavioral Statistics

linear model to demonstrate how different statistical methods are related to each other, Thompson integrates a broad array of methods involving;

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Regression and ANOVA

at Chapel Hill. The book focuses in the General Linear Model (GLM) theory, stated in matrix terms, which provides a more compact, clear, and;

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Univariate and Multivariate General Linear Models

both general linear model theory and application. The model is discussed using a general framework, enabling students to appreciate fully the;

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Analysis of Variance, Design, and Regression

generalized linear models R, Minitab (R), and SAS code on the author's website The text can be used in a variety of courses, including a;

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Analysis of Variance, Design, and Regression

SAS code on the author's website The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA;

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Introducing Anova and Ancova

Traditional approaches to ANOVA and ANCOVA are now being replaced by a General Linear Modeling (GLM) approach. This book begins with a;

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SAS Statistics by Example

, ANOVA, correlation, linear and multiple regression, analysis of categorical data, logistic regression, nonparametric techniques, and power and;

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SAS Statistics by Example

, ANOVA, correlation, linear and multiple regression, analysis of categorical data, logistic regression, nonparametric techniques, and power and;

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Statistical Methods for the Analysis of Biomedical Data

regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and;

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Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set

This set contains: 9780471469438 Regression and ANOVA: An Integrated Approach Using SAS(R) Software by Keith E. Muller, Bethel A. Fetterman;

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Univariate and Multivariate General Linear Models

Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory;

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Univariate and Multivariate General Linear Models

Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory;

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Theory Of Preliminary Test And Stein-Type Estimation With Applications

various topics, including: Simple linear model; ANOVA; parallelism model; multiple regression model with non-stochastic and stochastic;

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ANOVA and ANCOVA

contemporary look at the general linear model (GLM) approach to the analysis of variance (ANOVA) of one- and two-factor psychological experiments. With;

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The Coordinate-Free Approach to Linear Models

This book is about the coordinate-free, or geometric, approach to the theory of linear models; more precisely, Model I ANOVA and linear;

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Statistics In A Nutshell

of analysis appropriate to dichotomous, categorical, and continuous variables Advanced inferential techniques - Learn the General Linear Model;

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Applied Linear Statistical Models

. One is a two-term sequence focusing on regression followed by ANOVA/Experimental design. Applied Linear Statistical Models serves that market;

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Linear Models and TimeSeries Analysis

, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA), univariate time series;

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Applied Linear Regression 4th Ed

Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression;

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An Introduction to Generalized Linear Models

Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive;

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Regression Analysis and Linear Models

As a part of statistical modeling, regression analysis is the process and technique of understanding the relationship between dependent and;

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Statistical Modeling and Computation

II, the authors introduce a wide variety of classical models that include, among others, linear regression and ANOVA models. In Part III, the;

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Confidence Intervals in Generalized Regression Models

a number of different regression models, from very simple to more complex ones. It covers the general linear model (GLM), nonlinear;

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Confidence Intervals in Generalized Regression Models

a number of different regression models, from very simple to more complex ones. It covers the general linear model (GLM), nonlinear;

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