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Applied Manova and Discriminant Analysis

, Applied Discriminant Analysis, reflects and references current usage with its new title, Applied MANOVA and Discriminant Analysis. Thoroughly;

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Applied Statistics

in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression;

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Applied Multivariate Statistical Analysis - Summaries of theory and Exercises solved

rotation), Analysis of Hierarchical Cluster, Discriminant Analysis, and Single and Multiple Correspondence Analysis. The Minitab Statistical;

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Non-Asymptotic Analysis of Approximations for Multivariate Statistics

coefficients, MANOVA tests and discriminant functions studied in recent papers. It then introduces new areas of research in high-dimensional;

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Multivariate Analysis of Variance

flexible methodology for testing differences among means. This monograph considers the multivariate form of analysis of variance (MANOVA) and;

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Reading and Understanding Multivariate Statistics

, analysis of cross-classified data, logistic regression, multivariate an alysis of variance (MANOVA), discriminant analysis, and meta-analysis;

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Applied Multivariate Research

encounter, using a conceptual, non-mathematical, approach. Addressing correlation, multiple regression, exploratory factor analysis, MANOVA, path;

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Univariate and Multivariate General Linear Models

Researchers and students of applied statistics and the social and behavioral sciences will find this book indispensable for understanding;

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Applied Univariate, Bivariate, and Multivariate Statistics Using Python - A Beginner's Guide to Advanced Data Analysis

introduction to topics such as ANOVA, MANOVA and discriminant analysis, regression, principal components analysis, factor analysis, cluster analysis;

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Applied Multivariate Research

analysis, MANOVA, path analysis and structural equation modeling. This book is designed to provide full coverage of the wide range of multivariate;

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Crop Yield Forecasting Using Discriminant Function Analysis

, minimum temperature, rainfall and morning relative humidity. Discriminant function technique has been used for developing the forecast models;

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Approaching Multivariate Analysis

scalingPath analysis, and mediation and moderation analysisDiscriminant analysis;

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DATA MINING and MACHINE LEARNING. CLASSIFICATION PREDICTIVE TECHNIQUES: SUPPORT VECTOR MACHINE, LOGISTIC REGRESSION, DISCRIMINANT ANALYSIS and DECISION TREES

Vergelijkbare producten zoals DATA MINING and MACHINE LEARNING. CLASSIFICATION PREDICTIVE TECHNIQUES: SUPPORT VECTOR MACHINE, LOGISTIC REGRESSION, DISCRIMINANT ANALYSIS and DECISION TREES

Statistical Data Analysis and Entropy

. In multivariate statistical analysis, canonical correlation analysis, T2-statistic, and discriminant analysis are discussed in terms of entropy.;

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Robust Methods for Data Reduction

analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis. The first part of the;

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Robust Methods for Data Reduction

analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis. The first part of the book;

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Statistical Data Analysis and Entropy

. In multivariate statistical analysis, canonical correlation analysis, T2-statistic, and discriminant analysis are discussed in terms of entropy. Moreover;

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Ranking of Multivariate Populations

designs widely applied in research and industry investigations, such as multivariate analysis of variance (MANOVA) and multivariate randomized;

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Business Statistics Using R

, exponential smoothing, univariate and multivariate analysis including ANOVA and MANOVA and more in this valuable reference for policy makers;

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Pattern Recognition

discriminant analysis, feature extraction, error estimation, cluster analysis (together sometimes called statistical pattern recognition), grammatical;

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IBM SPSS Statistics 26 Step by Step

of statistical analysis and addresses more advanced topics such as multi-dimensional scaling, factor analysis, discriminant analysis, measures;

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A Step-by-Step Approach to Using SAS for Univariate and Multivariate Statistics

, guides readers step by step through the basic concepts of research and data analysis, to data input, and on to ANOVA (analysis of variance) and;

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Pattern Recognition in Biology

subdisciplines like discriminant analysis, feature extraction, error estimation, cluster analysis (together sometimes called statistical pattern;

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Discriminant Equations In Diophantine Nu

approximation and Diophantine geometry. This book is the first comprehensive account of discriminant equations and their applications. It brings;

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Applied Multivariate Statistics for the Social Sciences

of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New;

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Applied Multivariate Statistics for the Social Sciences

regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated;

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Advanced Statistics in Research

, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more. Advanced Statistics in Research;

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