Bohr Atomic Models Books
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
Isotope, Mass number, atomic number
Author: Odewole
School: University of Nigeria, Nsukka
Department: Science and Technology
Course Code: CHM101
Topics: Isotope, Mass number, atomic number, Dual nature of matter, photoelectric effect, atomic spectrum, Rydberg equation
Lecture note on atomic and nuclear physics
Author: Gentle soul
School: University of Ilorin
Department: Science and Technology
Course Code: PHY142
Topics: thompson, rutherford, bohr, electron, millkan, wave
Author: Maliki
School: Edo University
Department: Science and Technology
Course Code: CHM111
Topics: atomic theory, atoms, Joseph John Thomson atomic model, cathode ray tube, Plum-pudding model, electromagnetic spectrum, subatomic particles, atomic number, mass number, relative atomic mass, mass spectrometer, mass spectra, isotopes, periodic law, transition element, Ionizations energy, electronegativity, atomic radius, ionic radius, electronic configuration, wave mechanical model, quantum numbers, electronic configuration of elements, Heisenberg uncertainty principle, Pauli's exclusion principle, Hund's rule, Aufbau‟s principle, atomic model hybridization, chemical symbols, chemical formula, molecular formula, structural formula, chemical equations, stoichiometry, mole concept, Avogadro's number, gram formula mass, gas laws, Boyle's law, Charles law, general gas equation, standard temperature and pressure, electrochemistry, cell notation, Standard Electrode Potentials, electrochemical, Daniel cell, cell potential electrolysis, reduction reaction, oxidation reaction, oxidation number, REDOX equation, chemical equilibrium, Lechatelier's Principle, solution chemistry, solubility, Raoult's law, nuclear reaction, radioactivity, Alpha rays, Beta rays, Gamma rays, natural radioactive decay series, thorium series, uranium series, actinium series, neptunium series
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
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 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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