Linear Operator Statistical Representation Books
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
A First Course in Linear Algebra
Author: Robert Beezer
School: Edo University
Department: Science and Technology
Course Code: MTH214
Topics: Linear algebra, vector, Reduced Row-Echelon Form, vector operations, linear combinations, spanning sets, linear independence, orthogonality, matrices, matrix operation, matrix multiplication, matrix inverses, vector spaces, subspaces, matrix determinants, Eigenvalues, Eigen vectors, linear transformations, Injective Linear Transformations, Surjective Linear Transformations, Invertible Linear Transformations, vector representations, matrix representations, complex number operations, sets
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
Introduction to digital image processing
Author: William Pratt
School: National Open University of Nigeria
Department: Science and Technology
Course Code: CIT891
Topics: digital image processing, Continuous Image Mathematical Characterization, Continuous Image Characterization, light perception, eye physiology, visual phenomena, monochrome vision model, Photometry, Colorimetry, color matching, color spaces, image sampling, image reconstruction, Monochrome Image Sampling Systems, Monochrome Image Reconstruction Systems, Color Image Sampling Systems, image measurement, Discrete Image Mathematical Characterization, Vector-Space Image Representation, Generalized Two-Dimensional Linear Operator, Image Statistical Characterization, Image Probability Density Models, Linear Operator Statistical Representation, Finite-Area Superposition, Finite-Area Convolution, Sampled Image Superposition, Sampled Image Convolution, Circulant Superposition, circulant Convolution, General Unitary Transforms, Fourier transform, cosine transform, sine transform, Hartley transform, Hadamard Transforms, Haar Transforms, Daubechies Transforms, Karhunen–Loeve Transform, wavelet transforms, Linear Processing Techniques, Transform Domain Processing, Transform Domain Superposition, Fast Fourier Transform Convolution, Fourier Transform Filtering, image improvement, Image Enhancement, Contrast Manipulation, Histogram Modification, noise cleaning, Edge Crispening, Color Image Enhancement, Multispectral Image Enhancement, image restoration, image restoration models, Continuous Image Spatial Filtering Restoration, Pseudoinverse Spatial Image Restoration, Statistical Estimation Spatial Image Restoration, Multi-Plane Image Restoration, Geometrical Image Modification, Morphological Image Processing, binary image, Edge Detection, Image Feature Extraction, Image Segmentation, shape analysis, Image Detection, image Registration, Point Processing Image Compression, image compression, video compression, Spatial Processing Image Compression
Linear And Nonlinear Programming, 4th Edition
Author: David Luenberger, Yinyu Ye
School: Federal University of Technology, Owerri
Department: Engineering
Course Code: ENG308
Topics: Linear programming, simplex method, linear programs, Duality, Complementarity, interior-point methods, conic linear programming, unconstrained problems, concave functions, convex functions, speed of convergence, quasi-newton methods, constrained minimization, penalty method, barrier method, duality method, dual method, primal-dual method
Statistical Methods in Medical Research
Author: Charan Singh Rayat
School: University of Ilorin
Department: Science and Technology
Course Code: STA201
Topics: Theories of Probability, priori probability, Axiomatic theory of probability, Collecting Statistical Data, Tabulated Presentation of Data, Diagrammatic Presentation of Data, Graphic Presentation of Data, Central Tendency, Dispersion, Dispersion, Correlation, Chi-Square Test, Normal Curve, Sampling Distribution, Normal Distribution, Statistical Decision, Variance-Ratio Test, Analysis of Variance, ANOVA, Nonparametric Statistical Tests, Statistical Quality Control in Clinical Laboratories, Quality Control Measures, Applications of Microsoft Excel in Statistical Methods
Schaums Outline of Linear Algebra, 6th Edition
Author: Seymour Lipschutz, Marc Lipson
School: Edo University
Department: Science and Technology
Course Code: MTH214
Topics: Linear Algebra, Matrix algebra, matrix multiplication, Equivalent Systems, Elementary Operations, Gaussian Elimination, Echelon Matrices, Row Canonical Form, Row Equivalence, Matrix Formulation, Elementary Matrices, LU Decomposition, vector spaces, Linear Combinations, spanning sets, Full Rank Factorization, Least Square Solution, linear mappings, Cauchy–Schwarz Inequality, Gram–Schmidt Orthogonalization, determinants, diagonalization, Eigenvalues, Eigenvectors, Cayley–Hamilton Theorem, canonical forms, linear functionals, dual space, bilinear form, quadratic forms, Hermitian Form, linear operators
Author: MAT212
School: University of Ibadan
Department: Science and Technology
Course Code: MAT212
Topics: Linear Algebra, Algebra of Matrices, matrix, Determinants, Matrix Inverse, Systems of Linear Equations, Vector Space, linear equation, Subspaces of Vector Spaces, Rank of a Matrix, Linear Transformations, Linear Transformation, Homogeneous Systems of Linear Equations, Non-Homogeneous Systems of Linear Equations, Eigenvalue, Eigenvector, Minimal Polynomial, Matrix Polynomial, Companion Matrix, Similar Matrix, Diagonal Matrix, Triangular Matrix
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
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