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Segmented Regression Books

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

Elements of econometrics

Author: Dougherty

School: National Open University of Nigeria

Department: Administration, Social and Management science

Course Code: ECO356

Topics: Elements of econometrics, Simple regression analysis, econometrics, regression analysis, regression coefficients, hypothesis testing, Multiple regression analysis, Transformations of variables, Dummy variables, regression variables, Heteroscedasticity, Stochastic regressors, measurement errors, Simultaneous equations estimation, Binary choice, limited dependent variable models, maximum likelihood estimation, time series data, nonstationary time series, panel data, Regression analysis, linear algebra primer

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

Correlation and simple regression (Lecture note 5)

Author: MK Garba

School: University of Ilorin

Department: Science and Technology

Course Code: STA204

Topics: Correlation, simple regression, Correlation Analysis, Scatter Plot, Correlation Coefficient

Regression Analysis( lecture note 5)

Author: MK Garba

School: University of Ilorin

Department: Science and Technology

Course Code: STA204

Topics: Scatter Diagram, Regression Analysis

Applied Numerical Methods with MATLAB, 4th edition

Author: Steven Chapra

School: Edo University

Department: Engineering

Course Code: GEE216

Topics: Numerical Methods, mathematical modeling, MATLAB, mathematical operations, structured programming, errors, roundoff errors, truncation errors, total numerical errors, blunders, model errors, data uncertainty, roots, graphical methods, bracketing methods, bisection, roots, Simple Fixed-Point Iteration, Newton-Raphson, secant methods, Brent's method, MATLAB functions, optimization, linear systems, linear algebraic equations, matrices, Gauss elimination, Naive gauss elimination, tridiagonal systems, LU factorization, matrix inverse, system condition, error analysis, iterative methods, linear systems, nonlinear systems, Eugen values, power method, curve fitting, linear regression, random numbers, linear least-squares regression, polynomial regression, multiple linear regression, QR factorization, nonlinear regression, Fourier analysis, Continuous Fourier series, frequency domain, time domain, Fourier integral, Fourier transform, Discrete Fourier transform, power spectrum, polynomial interpolation, Newton interpolating polynomial, Lagrange interpolating polynomial, inverse interpolation, extrapolation, oscillations, splines, linear splines, quadratic splines, cubic spline, multidimensional interpolation, integration, differentiation, Numerical integration formulas, Newton-Cotes formulas, Trapezoidal rule, Simpson's rules, initial value problem, Runge-Kutta methods, adaptive Runge-Kutta methods, stiff systems, Boundary-value problems, shooting method, finite-difference methods, MATLAB function

Sampling ,3rd edition

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

Numerical methods for engineers ,8th edition

Author: Steven Chapra, Raymond Canale

School: University of Uyo

Department: Engineering

Course Code: GRE411

Topics: Mathematical Modeling, Engineering Problem Solving, Programming, Software, structured programming, Modular Programming, EXCEL, MATLAB, Mathcad, Significant Figures, accuracy, precision, error, Round-Off Errors, Truncation Errors, Taylor Series, Bracketing Methods graphical method, bisection method, False-Position Method, Simple Fixed-Point Iteration, Newton-Raphson Method, secant method, Brent’s Method, multiple roots, Roots of Polynomials, Müller’s Method, Bairstow’s Method, Roots of Equations pipe friction, Gauss Elimination, Naive Gauss Elimination, complex systems, Gauss-Jordan, LU Decomposition, Matrix Inversion, Special Matrices, Gauss-Seidel, Linear Algebraic Equations, Steady-State Analysis, One-Dimensional Unconstrained Optimization, Parabolic Interpolation, Golden-Section Search, Multidimensional Unconstrained Optimization, Constrained Optimization, linear programming, Nonlinear Constrained Optimization, Least-Squares Regression, linear regression, polynomial regression, Multiple Linear Regression, Nonlinear Regression, Linear Least Squares, interpolation, Newton’s Divided-Difference Interpolating Polynomials, Lagrange Interpolating Polynomials, Inverse Interpolation, Spline Interpolation, Multidimensional Interpolation, Fourier Approximation, Curve Fitting, Sinusoidal Functions, Continuous Fourier Series, Fourier Integral, Fourier Transform, Discrete Fourier Transform, Fast Fourier Transform, power spectrum, Newton-Cotes Integration Formulas, Trapezoidal Rule, Simpson’s Rules, multiple integrals, Newton-Cotes Algorithms, Romberg Integration, Adaptive Quadrature, Gauss Quadrature, Improper Integrals, Monte Carlo Integration, Numerical Differentiation, High-Accuracy Differentiation Formulas, Richardson Extrapolation, partial derivatives, Numerical Integration, Runge-Kutta Method, Euler’s Method, Boundary-Value Problems, Eigenvalue Problems, Finite Difference, Elliptic Equations, Laplace equation, Boundary Condition, Heat-Conduction Equation, Crank-Nicolson Method, Finite-Element Method

Modern elementary statistics ,12th edition

Author: John Freund, Benjamin Perles

School: University of Ibadan

Department: Science and Technology

Course Code: STA121

Topics: statistics, summarizing data, listing, grouping, Numerical data, Stem-and-Leaf Displays, frequency distribution, graphical presentations, Summarizing Two-Variable Data, population, sample, mean, weighted mean, median, mode, grouped data, measures of variation, range, standard deviation, variance, posibility, probability, counting, permutation, combination, sample spaces, events, odds, conditional probability, multiplication rules, Bayes theorem, Mathematical Expectation, expectation, decision, decision making, Statistical Decision Problems, Random Variable, probability distributions, binomial distributions, hypergeometric distributions, Poisson distribution, Multinomial distribution, Mean of a Probability Distribution, Standard Deviation of a Probability Distribution, normal distribution, Continuous Distributions, sampling, random sampling, sample designs, systematic sampling, stratified sampling, cluster sampling, sampling distribuions, central limit theorem, estimation, Tests of Hypotheses, Significance Tests, One-Way Analysis of Variance, analysis of variance, Multiple Comparisons, Two-Way Analysis of Variance, Design of Experiments, Design of Experiments, regression, Curve Fitting, Regression Analysis, Multiple Regression, Nonlinear Regression, Coefficient of Correlation, correlation, Correlation Analysis, Multiple Correlation, Partial Correlation, Nonparametric tests, sign test, signed-rank test, U test, H test, Tests of Randomness, Rank Correlation

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

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