Regression Analysis Books
Introduction to Linear Regression Analysis ,5th edition
Author: Elizabeth Peck, Geoffrey Vining, Douglas Montgomery
School: University of Ibadan
Department: Science and Technology
Course Code: STA351
Topics: Linear Regression Analysis, Regression, Model Building, Data Collection, Simple Linear Regression Model, Simple Linear Regression, Least-Squares Estimation, Hypothesis Testing, Interval Estimation, Multiple Regression Models, Multiple linear regression, Hypothesis Testing, Confidence Intervals, Standardized Regression Coefficients, Multicollinearity, Residual Analysis, model adequacy checking, Variance-Stabilizing Transformations, Generalized Least Squares, Weighted Least Squares, Regression Models, subsampling, Leverage, Measures of Influence, influence, Polynomial regression Models, Piecewise Polynomial Fitting, Nonparametric Regression, Kernel Regression, Locally Weighted Regression, Orthogonal Polynomials, Indicator Variables, Multicollinearity, Multicollinearity Diagnostics, Model-Building, regression models, Linear Regression Models, Nonlinear Regression Models, Nonlinear Least Squares, Logistic Regression Models, Poisson regression, Time Series Data, Detecting Autocorrelation, Durbin-Watson Test, Time Series Regression, Robust Regression, Inverse Estimation
Introduction to Linear Regression Analysis Solutions Manual for 5th edition
Author: Ann Ryan, Douglas Montgomery, Elizabeth Peck, Geoffrey Vining
School: University of Ibadan
Department: Science and Technology
Course Code: STA351
Topics: Linear Regression Analysis, Regression, Model Building, Data Collection, Simple Linear Regression Model, Simple Linear Regression, Least-Squares Estimation, Hypothesis Testing, Interval Estimation, Multiple Regression Models, Multiple linear regression, Hypothesis Testing, Confidence Intervals, Standardized Regression Coefficients, Multicollinearity, Residual Analysis, model adequacy checking, Variance-Stabilizing Transformations, Generalized Least Squares, Weighted Least Squares, Regression Models, subsampling, Leverage, Measures of Influence, influence, Polynomial regression Models, Piecewise Polynomial Fitting, Nonparametric Regression, Kernel Regression, Locally Weighted Regression, Orthogonal Polynomials, Indicator Variables, Multicollinearity, Multicollinearity Diagnostics, Model-Building, regression models, Linear Regression Models, Nonlinear Regression Models, Nonlinear Least Squares, Logistic Regression Models, Poisson regression, Time Series Data, Detecting Autocorrelation, Durbin-Watson Test, Time Series Regression, Robust Regression, Inverse Estimation
Regression and Analysis of Variance I
Author: Alaba Oluwayemisi Oyeronke
School: University of Ibadan
Department: Science and Technology
Course Code: STA322
Topics: Regression, Analysis of Variance, Correlation Coefficient, Correlation Ratio, Simple Linear Regression, Multiple Linear Regression, Multiple Regression Analysis, Polynomial Regression, Non-Linear Regression Model, ANOVA, Randomized Complete Block Design, Analysis of Variance for Randomized Complete Block Design, Latin Square Design, Least Significant Difference
Basic Econometrics ,Fifth Edition
Author: Damodar Gujarati, Dawn Porter
School: Modibbo Adama University of Technology
Department: Administration, Social and Management science
Course Code: CC312
Topics: Single-Equation Regression Models, Regression Analysis.Two-Variable Regression Analysis, Two-Variable Regression Model, Classical Normal Linear Regression Model, Two-Variable Regression, Interval Estimation, Hypothesis Testing, Multiple Regression Analysis, Dummy Variable Regression Models, Multicollinearity, Heteroscedasticity, Autocorrelation, Econometric Modeling, Nonlinear Regression Model, Qualitative Response Regression Models, Panel Data Regression Models, Dynamic Econometric Models, Autoregressive Lag Models, Distributed-Lag Models, Simultaneous-Equation Models, Time Series Econometrics, Simultaneous-Equation Models, Identification Problem, Simultaneous-Equation Methods, Time Series Econometrics, Time Series Econometrics, Forecasting, econometrics
Basic econometrics Student solutions manual for use with Basic econometrics
Author: Damodar Gujarati, Dawn Porter
School: Modibbo Adama University of Technology
Department: Administration, Social and Management science
Course Code: CC312
Topics: econometrics, Single-Equation Regression Models, Regression Analysis.Two-Variable Regression Analysis, Two-Variable Regression Model, Classical Normal Linear Regression Model, Two-Variable Regression, Interval Estimation, Hypothesis Testing, Multiple Regression Analysis, Dummy Variable Regression Models, Multicollinearity, Heteroscedasticity, Autocorrelation, Econometric Modeling, Nonlinear Regression Model, Qualitative Response Regression Models, Panel Data Regression Models, Dynamic Econometric Models, Autoregressive Lag Models, Distributed-Lag Models, Simultaneous-Equation Models, Time Series Econometrics, Simultaneous-Equation Models, Identification Problem, Simultaneous-Equation Methods, Time Series Econometrics, Time Series Econometrics, Forecasting
Econometric Analysis ,8th edition
Author: William Greene
School: National Open University of Nigeria
Department: Administration, Social and Management science
Course Code: ECO454
Topics: Linear Regression Model, Econometrics, Least Squares Regression, Hypothesis Tests, Model Selection, Functional Form, Difference in Differences, Structural Change, Nonlinear Regression Models, Semiparametric Regression Models, Nonparametric Regression Models, Endogeneity, Instrumental Variable Estimation, Generalized Regression Model, Heteroscedasticity, Regression Equations, Estimation Frameworks, Estimation Methodology, Minimum Distance Estimation, Generalized Method of Moments, Maximum Likelihood Estimation, Simulation-Based Estimation, Inference, Random Parameter Models, Bayesian Estimation, Cross Sections, Panel Data, Microeconometrics, Binary Outcomes, Discrete Choices, Multinomial Choices, Event Counts, Limited Dependent Variables—Truncation, Censoring, Sample Selection, Time Series, Macroeconometrics, Serial Correlation, Nonstationary Data
Applied Linear Statistical Models 5th Edition Instructors Solutions Manual
Author: Michael Kutner, Christopher Nachtsheim, John Neter, William Li
School: University of Ibadan
Department: Science and Technology
Course Code: STA322
Topics: Linear Statistical Models, linear regression, inference, correlation analysis, simultaneous inferences, regression analysis, simple linear regression analysis, multiple regression, quantitative predictors, qualitative predictors, regression, model, autocorrelation, time series, nonlinear regression, Neural networks, Logistic regression, Possion regression, Generalized linear models, ANOVA, Two-factor analysis of variance, two-factor studies, randomized complete block designs, analysis of covariance, multifactor studies, Nested designs, subsampling, partially nested designs
Applied Linear Statistical Models,5th edition
Author: Michael Kutner, Christopher Nachtsheim, John Neter, William Li
School: University of Ibadan
Department: Science and Technology
Course Code: STA322
Topics: Linear Statistical Models, linear regression, inference, correlation analysis, simultaneous inferences, regression analysis, simple linear regression analysis, multiple regression, quantitative predictors, qualitative predictors, regression, model, autocorrelation, time series, nonlinear regression, Neural networks, Logistic regression, Possion regression, Generalized linear models, ANOVA, Two-factor analysis of variance, two-factor studies, randomized complete block designs, analysis of covariance, multifactor studies, Nested designs, subsampling, partially nested designs
Regression Analysis( lecture note 5)
Author: MK Garba
School: University of Ilorin
Department: Science and Technology
Course Code: STA204
Topics: Scatter Diagram, Regression Analysis
Author: Samuel Olumuyiwa Olusanya
School: National Open University of Nigeria
Department: Administration, Social and Management science
Course Code: ECO355
Topics: Econometrics, Econometrics Model, Linear Regression, Regression Analysis, Ordinary Least Square Method Estimation, Classical Least Regression Method, Ordinary Least Square Estimators, Coefficient of Determination, Classical Normal Linear Regression Model, NORMAL LINEAR REGRESSION MODEL, SINGLE- EQUATION REGRESSION MODELS, ECONOMETRICS ANALYSIS, Method Of Maximum Likelihood, Confidence intervals, Regression Coefficients, Regression Analysis, Analysis of Variance, Normality
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