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Relationship Inference with Familias and R

Relationship Inference in Familias and R discusses the use of Familias and R software to understand genetic kinship of two or more DNA;

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An Introduction to Statistical Inference and Its Applications with R

Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition;

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An Introduction to Statistical Inference and Its Applications with R

Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition;

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Familias Ensambladas Softcover Blended Families

Familias ensambladas (Blended Families) tells about the experience of a marriage that brought to their relationship more than love for each;

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Statistics for Astrophysics

This book contains statistics courses on basic to advanced methods with practical exercises using the R environment, by leading experts;

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Bayesian inference with INLA

a wide range of models with R. Topics covered include generalized linear mixed-effects models, multilevel models, spatial and spatio;

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Bayesian inference with INLA

a wide range of models with R. Topics covered include generalized linear mixed-effects models, multilevel models, spatial and spatio;

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Linear Statistical Inference And Its Applications

. Efrom Translated into six major languages of the world, C. R. Rao's Linear Statistical Inference and Its Applications is one of the foremost;

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Information, Inference and Decision

of inductive behaviour, on the basis of R. A. Fisher's statistical inference philosophy, on the one hand, and R. Carnap's inductive logic, on the other;

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Analysis of Longitudinal Data with Examples

including likelihood-based approaches. The theory will be supported with practical examples of R-codes and R-packages applied to interesting case;

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Asymptotic Statistical Inference

for the goodness of fit and tests for contingency tables. The book also discusses a score test and Wald's test, their relationship with the;

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Asymptotic Statistical Inference

for the goodness of fit and tests for contingency tables. The book also discusses a score test and Wald's test, their relationship with the;

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La Crianza de los Hijos

estar trabajando en contra de las esperanzas y suenos que tienen los padres cristianos para sus familias. En este volumen tan necesitado;

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Introduction to Empirical Processes and Semiparametric Inference

Kosorok's brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful;

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Statistical Computing with R

feature R, Statistical Computing with R covers the traditional core material of computational statistics, with an emphasis on using the R language;

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R for Conservation and Development Projects

Simple English format Foundation sections on inference and evidence, and data integration in project management Exploration of R usage;

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R for Conservation and Development Projects

Simple English format Foundation sections on inference and evidence, and data integration in project management Exploration of R usage;

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Bayesian Inference for Stochastic Processes

Bayesian approach (including the optimal use of prior information). Initially, the book begins with a brief review of Bayesian inference and uses;

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Bayesian Inference for Stochastic Processes

Bayesian approach (including the optimal use of prior information). Initially, the book begins with a brief review of Bayesian inference and uses;

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference;

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference;

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Examples in Parametric Inference with R

This book discusses examples in parametric inference with R. Combining basic theory with modern approaches, it presents the latest;

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A Handbook of Statistical Analyses Using R

interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data.;

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Causality and Probability in the Sciences

relationship between causality and probability and the application of these concepts within the sciences. With its interdisciplinary perspective and;

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Basic Statistics with R

Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results;

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Inference Principles for Biostatisticians

pharmaceutical industry, the author explains the main principles of statistical inference with many examples and exercises. Extended examples illustrate;

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Inference Principles for Biostatisticians

pharmaceutical industry, the author explains the main principles of statistical inference with many examples and exercises. Extended examples illustrate;

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