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Regression Analysis and Its Application: A Data-Oriented Approach

Regression Analysis and Its Application: A Data-Oriented Approach answers the need for researchers and students who would like a better;

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Regression Analysis and its Application

Regression Analysis and Its Application: A Data-Oriented Approach answers the need for researchers and students who would like a better;

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Classroom Supplement to Regression Analysis and its Application

underlying the techniques utilized in regression analysis and illustrates their application on a variety of data sets.;

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Introductory Regression Analysis

equips students to derive the benefit and meaning of a regression analysis. This text is designed to serve in a second undergraduate course;

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Introductory Regression Analysis

equips students to derive the benefit and meaning of a regression analysis. This text is designed to serve in a second undergraduate course;

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Modeling in Mathematics

and its application to energy-growth consumption problem. This book also discusses about intuitionistic fuzzy weighted linear regression model;

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Analysis of Messy Data, Volume III

approach of treating the analysis of covariance problem by looking at a set of regression models, one for each of the treatments or treatment;

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R In Finance And Economics

This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics;

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Spatial Regression Analysis Using Eigenvector Spatial Filtering

Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation;

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Regression Analysis with Python

, who want to learn how to do regression analysis on a dataset. It is beneficial if you have some knowledge of statistics and data science;

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Business Applications of Multiple Regression

management and data analysis. This book on correlation and regression analysis will have a non-mathematical, applied, data-analytic approach. Readers;

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Multiple Regression And Beyond

Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis, along with more complex;

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Statistical Data Mining Using SAS Applications

regression multivariate methods, and classification analysis. It presents an accessible, SAS macro-oriented approach while offering comprehensive;

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Nonlinear Regression Analysis and Its Applications

. -Technometrics [This book] provides a good balance of relevant theory and application with many examples ...[and it] provides the most balanced approach;

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Data Analysis

Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond is an integrated treatment of data analysis for the social and;

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Data Analysis

Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond is an integrated treatment of data analysis for the social and;

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Logistic Regression Using SAS

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul;

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Regression Models for Categorical and Count Data

regression analysis on categorical and count data. The author covers both the theory and application of statistical models, with the help;

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Bayesian Modeling in Bioinformatics

error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for;

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Bayesian Modeling in Bioinformatics

error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for;

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Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications

, methodological as well as application-oriented articles in domains such as: Linear Models and Regression, Survival Analysis, Extreme Value Theory;

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Data Analysis

models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison;

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Conventional and Fuzzy Regression

a small sample of data. The seventh chapter refers to the multivariable crisp and fuzzy linear regression. In the application paradigm, the;

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Applied Regression Analysis for Business

supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world;

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Logistic Regression Using SAS

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul;

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Correlation and Regression Analysis

of Amortization which provide a basic understanding of the correlation and regression analysis. The application of these concepts to develop economic and;

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Applied Regression Analysis and Experimental Design

keeping computational and theoretical details at a manageable level, Applied Regression Analysis and Experimental Design features an emphasis on;

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