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Statistical Regression Modeling with R

of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling;

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Statistical Regression Modeling with R

of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling;

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Advanced R Statistical Programming and Data Models

, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to;

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Statistical Methods for Field and Laboratory Studies in Behavioral Ecology

regression and ANOVA. The objective is to teach students to recognize situations where various statistical methods should be used, understand the;

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Statistical Methods for Field and Laboratory Studies in Behavioral Ecology

regression and ANOVA. The objective is to teach students to recognize situations where various statistical methods should be used, understand the;

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Flexible Bayesian Regression Modelling

flexible (such as spline models). Each chapter discusses the key aspects of fitting a regression model. R programs accompany the methods;

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Statistical Application Development with R and Python -

preliminary concepts right away using R and Python. * Understand data modeling and visualization to perform efficient statistical analysis with this;

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An Introduction to Generalized Linear Models

framework for statistical modeling. This new edition of a bestseller has been updated with Stata, R, and WinBUGS code as well as three new chapters;

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Advanced Regression Models with SAS and R

Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book;

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Advanced Regression Models with SAS and R

Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book;

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Statistical Thinking in Epidemiology

in Epidemiology examines common methodological and statistical problems in the use of correlation and regression in medical and epidemiological research;

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Statistical Thinking in Epidemiology

in Epidemiology examines common methodological and statistical problems in the use of correlation and regression in medical and epidemiological research;

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R In Finance And Economics

This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics;

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Robust Nonlinear Regression

accompanying website Robust Nonlinear Regression: with Applications using R is an ideal text for statisticians, biostatisticians, and statistical;

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An R Companion to Applied Regression

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied;

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Regression Modeling with Actuarial and Financial Applications

with detailed descriptions, sample statistical software scripts in 'R' and 'SAS', and tips on writing a statistical report, including sample;

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Regression Modeling with Actuarial and Financial Applications

with detailed descriptions, sample statistical software scripts in 'R' and 'SAS', and tips on writing a statistical report, including sample;

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Introductory Statistics with R

methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way;

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R Statistics Cookbook

skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are;

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R for Marketing Research and Analytics

This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a;

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Modeling in Mathematics

Modeling in Mathematics deals with the concept of modeling in the field of mathematics. It includes a statistical and spectral model for;

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Beginning R 4

Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical;

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Statistical Power Analysis for the Social and Behavioral Sciences

techniques such as hierarchical linear modeling, meta-analysis, and structural equation modeling. Each chapter opens with a review of the statistical;

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Statistical Power Analysis for the Social and Behavioral Sciences

techniques such as hierarchical linear modeling, meta-analysis, and structural equation modeling. Each chapter opens with a review of the statistical;

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Pricing Analytics

from data. Specifically, itcomes from statistically modeling the data. This book gives the reader the statistical modeling tools needed to get;

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Pricing Analytics

from data. Specifically, itcomes from statistically modeling the data. This book gives the reader the statistical modeling tools needed to;

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Building Better Models with JMP Pro

Building Better Models with JMP(r) Pro provides an example-based introduction to business analytics, with a proven process that guides you;

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