biostatistics and computer based analysis of health data using r

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Biostatistics and Computer based Analysis of Health Data using R
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Publisher : Elsevier
Release Date :
ISBN 10 : 008101175X
Pages : 206 pages
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Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data. It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data. With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software. Features useful commands for describing a data table composed made up of quantitative and qualitative variables Includes measures of association encountered in epidemiological studies, odds ratio, relative risk, and prevalence Presents an analysis of censored data, the key main tests associated with the construction of a survival curve (log-rank test or Wilcoxon), and the Cox regression model

Biostatistics and Computer based Analysis of Health Data using R

Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data. It is therefore of primary importance to understand how statistical data is displayed and how

GET BOOK!
Biostatistics and Computer based Analysis of Health Data Using SAS

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models

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Biostatistics and Computer based Analysis of Health Data using Stata

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of Stata for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models

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Analyzing Health Data in R for SAS Users

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Biostatistics for Epidemiology and Public Health Using R

Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption

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Introduction to Data Science

Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization,

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