Simple Linear Regression Books
Author: Jörg Liesen, Volker Mehrmann
School: University of Ilorin
Department: Science and Technology
Course Code: MAT206, MAT213, PHY464, ELE576
Topics: algebraic structures, matrix, echelon form, Gaussian elimination, linear system, vector space, linear map, linear form, bilinear form, Euclidean vector space, unitary vector space, eigenvalue, endomorphism, polynomials, theory of algebra, cyclic subspace, duality, Jordan canonical form, matrix function, singular value decomposition, Kronecker product, linear matrix
Author: Kenneth kuttler
School: Modibbo Adama University of Technology
Department: Administration, Social and Management science
Course Code: CC316
Topics: Determinant Linear Algebra, Matrices, Linear Transformation, Linear Programming, Linear Equation Model, Input-Output Table, Production Functions, Isoquant, Isocost, Returns to Scale
Author: PHY
School: University of Ilorin
Department: Science and Technology
Course Code: PHY115
Topics: Simple Harmonic Motion, Simple Harmonic Oscillator, Period, Simple Pendulum
Introduction to Econometrics 2
Author: GA Adesina-Uthman, Okojie Daniel Esene
School: National Open University of Nigeria
Department: Administration, Social and Management science
Course Code: ECO356
Topics: Sampling Theory, Variance, Correlation, Econometrics, Random Variables, Sampling Theory, Covariance, Variance, Correlation, Regression Models, Hypothesis Testing, Dummy Variables.Simple Regression Analysis, Regression Coefficients, Multiple Regression Analysis, Multicollinearity, Transformations of Variables, regression variables, Heteroscedasticity/Heteroskedasticity, Autocorrelation, Error, Econometric Modelling, Stochastic Regression, measurement errors, Autocorrelation, Econometric Modelling, Time Series Data Models, Simultaneous Equation, Binary Choice, Maximum Likelihood Estimation
Linear Programming, 4th edition
Author: Robert Vanderbei
School: Federal University of Technology, Owerri
Department: Engineering
Course Code: ENG308
Topics: simplex method, degeneracy, duality theory, primal simplex method, Lagrangian duality, sensitivity analysis, parametric analysis, implementation issues, convex analysis, game theory, regression, structural optimization, interior-point methods, central path, Lagrange multipliers, path-following method, KKT system, affine-scaling, method, integer programming, quadratic programming, convex programming, Markowitz model
Introduction to Econometrics ,4th Global Edition
Author: James Stock, Mark Watson
School: National Open University of Nigeria
Department: Administration, Social and Management science
Course Code: ECO355, ECO356
Topics: Econometrics, economic questions, Regression Analysis, Linear Regression, Hypothesis Tests, Confidence Intervals, Multiple Regression, Nonlinear Regression Functions, Instrumental Variables Regression, Experiments, Quasi-Experiments, Time Series Regression, Forecasting
Probability and Statistics, The Science of Uncertainty, 2nd Edition
Author: Michael Evans, Jeffrey Rosenthal
School: Federal University of Technology, Owerri
Department: Science and Technology
Course Code: STA301
Topics: probability models, Conditional Probability, Venn diagram, Random Variables, Discrete Distributions, Continuous Distributions, Cumulative Distribution Functions, Joint Distributions, Simulating Probability Distributions, expectation, Inequalities, Jensen’s Inequality, Sampling Distributions, Limits, Central Limit Theorem, Monte Carlo Approximations, Normal Distribution Theory, Chi-Squared Distribution, Statistical Inference, statistical model, Data Collection, Finite Populations, Simple Random Sampling, Histograms, Survey Sampling, Descriptive Statistics, Plotting Data, Likelihood Inference, Maximum Likelihood Estimation, Distribution-Free Methods, Bayesian Inference, Bayesian Computations, Optimal Inferences, Optimal Unbiased Estimation, Optimal Hypothesis Testing, quantitative response, Simple Linear Regression Model, Bayesian Simple Linear Model, Multiple Linear Regression Model, Markov Chains, Gambler’s Ruin Problem, Markov Chain Monte Carlo, Martingales, Brownian Motion, Poisson Processes
Elementary statistics, 11th edition
Author: Robert Johnson, Patricia Kuby
School: Edo University
Department: Administration, Social and Management science
Course Code: ECO113
Topics: statistics, single-variable data, bivariate data, probability, probability distributions, discrete variables, normal probability distributions, sample variability, statistical inference, Chi-square, analysis of variance, linear correlation, regression analysis, nonparametric statistics, data collection, measurability, variability, measure of central tendency, linear correlation, linear regression, random variables, Binomial probability distribution, normal probability distributions, notation, sampling distributions, inferential statistics, Chi-square statistic, ANOVA, linear correlation analysis, linear regression analysis
Author: Steven Thompson
School: University of Ibadan
Department: Science and Technology
Course Code: STA351
Topics: Sampling, Sampling Units, Sampling errors, Nonsampling Errors, Simple Random Sampling, Confidence Intervals, Sample Size, Estimating Proportions, Estimating Ratios, Estimating Subpopulation Means, Unequal Probability Sampling, Horvitz-Thompson Estimator, Hansen–Hurwitz Estimator, Auxiliary Data, Ratio Estimation, Ratio Estimator, Small Population Illustrating Bias, Regression Estimation, Linear Regression Estimator, regression model, Multiple Regression Models, Regression Models, Stratified Sampling, Stratified Random Sampling, Cluster Sampling, Systematic Sampling, Multistage Designs, Double Sampling, Two-Phase Sampling, Network Sampling, Link-Tracing Designs, Detectability, Capture–Recapture Sampling, Line-Intercept Sampling, spatial sampling, Spatial Prediction, Kriging, Spatial Covariance Function, Spatial Designs, Adaptive Sampling Designs, Adaptive Sampling, Adaptive Cluster Sampling, Stratified Adaptive Cluster Sampling
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
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