Advanced Regression Analysis
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Advanced Regression Analysis
An Introduction
Cooper, Robert; Pollins, Brian Michael
Sage Publications Ltd
12/2030
224
Mole
Inglês
9781473912168
Pré-lançamento - envio 15 a 20 dias após a sua edição
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Chapter 1: Understanding and Applying Regression Analysis - Theory as Well as Practice
Chapter 2: Basic Matrix Algebra for Regression Analysis
Chapter 3: Ordinary Least Squares Regression Derived, and Initial Tenets of Estimation Practice Introduced
Chapter 4: Moving from Ordinary to Generalized Least Squares, Illustrated through the Problem of Heteroskedasticity
Chapter 5: Autocorrelated Errors - A Further Look at Generalized Least Squares
Chapter 6: Finding Unusual Cases in Your Data Set - They Aren't Just 'Outliers'
Chapter 7: Collinearity - Finding and Coping with Very High Correlations Among Explanatory Variables
Chapter 8: Model Specification - How Can We Know When a Model is Good, or Better than a Competing Model?
Chapter 9: Measurement Error in Our Independent and Dependent Variables - How Might This Compromise Your Parameter Estimates, And What Can You Do About It?
Chapter 10: Regression Analysis Is the Gateway - Some Directions for Further Study in Data Science
Chapter 2: Basic Matrix Algebra for Regression Analysis
Chapter 3: Ordinary Least Squares Regression Derived, and Initial Tenets of Estimation Practice Introduced
Chapter 4: Moving from Ordinary to Generalized Least Squares, Illustrated through the Problem of Heteroskedasticity
Chapter 5: Autocorrelated Errors - A Further Look at Generalized Least Squares
Chapter 6: Finding Unusual Cases in Your Data Set - They Aren't Just 'Outliers'
Chapter 7: Collinearity - Finding and Coping with Very High Correlations Among Explanatory Variables
Chapter 8: Model Specification - How Can We Know When a Model is Good, or Better than a Competing Model?
Chapter 9: Measurement Error in Our Independent and Dependent Variables - How Might This Compromise Your Parameter Estimates, And What Can You Do About It?
Chapter 10: Regression Analysis Is the Gateway - Some Directions for Further Study in Data Science
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regression analysis;matrix algebra;advanced regression analysis;statistics;data science;social science;political science
Chapter 1: Understanding and Applying Regression Analysis - Theory as Well as Practice
Chapter 2: Basic Matrix Algebra for Regression Analysis
Chapter 3: Ordinary Least Squares Regression Derived, and Initial Tenets of Estimation Practice Introduced
Chapter 4: Moving from Ordinary to Generalized Least Squares, Illustrated through the Problem of Heteroskedasticity
Chapter 5: Autocorrelated Errors - A Further Look at Generalized Least Squares
Chapter 6: Finding Unusual Cases in Your Data Set - They Aren't Just 'Outliers'
Chapter 7: Collinearity - Finding and Coping with Very High Correlations Among Explanatory Variables
Chapter 8: Model Specification - How Can We Know When a Model is Good, or Better than a Competing Model?
Chapter 9: Measurement Error in Our Independent and Dependent Variables - How Might This Compromise Your Parameter Estimates, And What Can You Do About It?
Chapter 10: Regression Analysis Is the Gateway - Some Directions for Further Study in Data Science
Chapter 2: Basic Matrix Algebra for Regression Analysis
Chapter 3: Ordinary Least Squares Regression Derived, and Initial Tenets of Estimation Practice Introduced
Chapter 4: Moving from Ordinary to Generalized Least Squares, Illustrated through the Problem of Heteroskedasticity
Chapter 5: Autocorrelated Errors - A Further Look at Generalized Least Squares
Chapter 6: Finding Unusual Cases in Your Data Set - They Aren't Just 'Outliers'
Chapter 7: Collinearity - Finding and Coping with Very High Correlations Among Explanatory Variables
Chapter 8: Model Specification - How Can We Know When a Model is Good, or Better than a Competing Model?
Chapter 9: Measurement Error in Our Independent and Dependent Variables - How Might This Compromise Your Parameter Estimates, And What Can You Do About It?
Chapter 10: Regression Analysis Is the Gateway - Some Directions for Further Study in Data Science
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
