Autocorrelation Books
Econometric Methods ,Fourth Edition
Author: Jack Johnston, John DiNardo
School: Modibbo Adama University of Technology
Department: Administration, Social and Management science
Course Code: CC312
Topics: Maximum Likelihood Estimation, k-variable Linear Equation, Partial Correlation Coefticients, Specilkation Error, Parameter Constancy, Dummy Variables, Maximum Likelihood, Generalized Least Squares, Instrumental Variable Estimators, heteroscedasticity, autocorrelation, Estimation Under Heteroscedasticity, Autocorrelated Disturbances, Univariate Time Series Modeling, Autoregressive Distributed Lag Relationships, Multiple Equation Models, Vector Autoregressions, Simultaneous Structural Equation Models, Panel Data
Author: Michael de Smith
School: University of Ibadan
Department: Science and Technology
Course Code: STA231, STA322, STA351, STA415
Topics: Statistical Analysis, statistical data, statistical method, sampling, sample size, data preparation, data cleaning, missing data, data errors, statistical error, probability theory, odds, risk, frequentist probability theory, Bayesian probability theory, probability distribution, statistical modelling, computational statistics, inference, bias, confounding, hypothesis testing, statistical significance, confidence intervals, Non-parametric analysis, descriptive statistics, measures of central tendency, statistical indices, key functions, matrix, data transformation, data standardization, Box-cox, power transforms, Freeman-turkey transform, log transform, exponential transforms, logit transform, Normal transform, Z-transform, data exploration, graphic, visualization, exploratory data analysis, randomness, randomization, random numbers, random permutations, correlation, autocorrelation, probability distributions, eestimations, estimators, Maximum likelihood estimation, Bayesian estimation, z-test, T-test, variance test, contigency tables, randomized block designs, factorial designs, Analysis of variance, Analysis of covariance, ANOVA, MANOVA, ANCOVA, regression, smoothing, time series analysis
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
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
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
Schaums outline of theory and problems of statistics and econometrics ,2nd edition
Author: Derrick Reagle, Dominick Salvatore
School: National Open University of Nigeria
Department: Administration, Social and Management science
Course Code: ECO450
Topics: statistics, econometrics, Descriptive Statistics, Frequency Distributions, Measures of Central Tendency, Measures of Dispersion, Probability, Probability Distributions, Discrete Probability Distributions, Binomial Distribution, Poisson Distribution, Continuous Probability Distributions, The Normal Distribution, Statistical Inference, Estimation, Sampling, Sampling Distribution, Statistical Inference, Testing Hypothesis, Analysis of Variance, Chi-Square Test, Nonparametric Testing, Simple Regression Analysis, Two-Variable Linear Model, Ordinary Least-Squares Method, Ordinary Least-Squares Estimators, Multiple Regression Analysis, Three-Variable Linear Model, Coefficient of Multiple Determination, Partial-Correlation Coefficients, Matrix Notation, Functional Form, Regression Analysis, Dummy Variables, Distributed Lag Models, Forecasting, Binary Choice Models, Multicollinearity, Heteroscedasticity, Autocorrelation, Simultaneous-Equations Methods, Time-Series Methods, ARMA
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