Amplifier Models Books
Electronics principles, 7th edition
Author: Albert Malvino, David Bates
School: Federal University of Technology, Owerri
Department: Engineering
Course Code: ECE411
Topics: Semiconductors, Diode Theory, Diode Circuits, Special-Purpose Diodes, BJT Fundamentals, BJT Biasing, BJT Amplifiers, Multistage Amplifiers, CC Amplifiers, CB Amplifiers, Power Amplifiers, JFETs, MOSFETs, Thyristors, Frequency Effects, Differential Amplifiers, Operational Amplifiers, Negative Feedback, Linear Op-Amp Circuit Applications, Active Filters, nonlinear op-amp circuit applications, oscilators, regulated power supplies
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
Author: TEXAS INSTRUMENTS
School: Federal University of Technology, Owerri
Department: Engineering
Course Code: ECE316
Topics: Operational Amplifier, OPAMP, Comparators, Multivibrators, DC Amplifiers, Summing Amplifiers, Integrator, Differentiators, Filters
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
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
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