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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

Generalized Linear Models ,2nd Edition

Author: McCullagh, John Nelder

School: University of Ibadan

Department: Science and Technology

Course Code: STA351

Topics: Generalized Linear Models, dilution assay, probit analysis, logit models, log-linear models, inverse polynomical, survival data, model fittinf, residuals, pearson residual, Anscombe residual, deviance residual, error structure, systemic component, aliasing, estimation, tables, binary data, binomial distribution, over-dispersion, measurement scales, multinomial distribution, likelihood functions, log-linear models, multiple responses, conditional likelihoods, hypergeometric distributions, Gamma distribution, Quasi-likelihood functions, dependent observations, optimal estimating functions, optimality criteria, model checking, survival data, dispersion

Applied Econometrics ,2nd edition

Author: Dimitrios Asteriou, Stephen Hall

School: National Open University of Nigeria

Department: Administration, Social and Management science

Course Code: ECO355

Topics: Applied Econometrics, Econometrics, Economic Data, Basic Data Handling, Simple Regression, Classical Linear Regression Model, Multiple Regression, Multicollinearity, Heteroskedasticity, Autocorrelation, Misspecification, Wrong Regressors, Measurement Errors, Wrong Functional Forms, Dummy Variables, Dynamic Econometric Models, Simultaneous Equation Models, Limited Dependent Variable Regression Models, Time Series Econometrics, ARIMA Models, Box–Jenkins Methodology, ARCH model, GARCH model, Vector Autoregressive Models, Causality Tests, Non-Stationarity Tests, Unit-Root Tests, Cointegration, Error-Correction Models, Solving Models, Panel Data Econometrics, Panel Data Models, Dynamic Heterogeneous Panels, Non-Stationary Panels, Econometric Software

An introduction to generalized linear models ,4th edition

Author: Annette Dobson, Adrian Barnett

School: University of Ibadan

Department: Science and Technology

Course Code: STA351

Topics: generalized linear models, Model Fitting, Exponential Family, estimation, inference, normal linear models, Binary Variables, Logistic Regression, Nominal Logistic Regression, Ordinal Logistic Regression, Poisson Regression, Log-Linear Models, Survival Analysis, Clustered data, Longitudinal Data, Bayesian Analysis, Markov Chain Monte Carlo Methods

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

Modern Social Work Theory

Author: Malcolm Payne

School: University of Ibadan

Department: Administration, Social and Management science

Course Code: SOW303

Topics: Social Work Theory, Social worker, Work, Psychodynamic Models, Crisis Intervention, Task-centred practice, Behavioural Models, Models, Systems, Ecological Models, Social Psychology, Humanist Models, Existential Models, Cognitive Models, Empowerment, Advocacy

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

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