000			04661nam a22001817a 4500
020			_a9781482204582
082			_a519.50285 HOT
100			_aHothorn, Torsten _aEveritt, Brain S
245			_aHandbook of statistical analyses using R
250			_a3
260			_aNew York _bCRC Press _c2014
300			_axxiv,421p. _b23cm; Soft
500			_aAlpha 1040/02 Jan 15 Rs.4023/-
505			_aTable of Contents Introduction Density Estimation Analysis Using R Summary of Findings Final Comments Recursive Partitioning Introduction Recursive Partitioning Analysis Using R Summary of Findings Final Comments 　　　 Scatterplot Smoothers and Additive Models Introduction 　　　 Scatterplot Smoothers and Generalised Additive Models 　　　 Analysis Using R 　　　 Summary of Findings Final Comments Survival Analysis Introduction 　　　 Survival Analysis 　　　 Analysis Using R 　　　 Summary of Findings Final Comments 　　　 Quantile Regression Introduction 　　　 Quantile Regression 　　　 Analysis Using R 　　　 Summary of Findings 　　　 Final Comments 　　　 Analysing Longitudinal Data I Introduction 　　　 Analysing Longitudinal Data 　　　 Linear Mixed Effects Models 　　　 Analysis Using R 　　　 Prediction of Random Effects 　　　 The Problem of Dropouts 　　　 Summary of Findings 　　　 Final Comments Analysing Longitudinal Data II Introduction 　　　 Methods for Non-Normal Distributions 　　　 Analysis Using R: GEE 　　　 Analysis Using R: Random Effects Summary of Findings 　　　 Final Comments 　　　 Simultaneous Inference and Multiple Comparisons Introduction 　　　 Simultaneous Inference and Multiple Comparisons 　　　 Analysis Using R 　　　 Summary of Findings 　　　 Final Comments Missing Values Introduction 　　　 The Problems of Missing Data 　　　 Dealing with Missing Values 　　　 Imputing Missing Values 　　　 Analyzing Multiply Imputed Data 　　　 Analysis Using R 　　　 Summary of Findings 　　　 Final Comments Meta-Analysis Introduction 　　　 Systematic Reviews and Meta-Analysis 　　　 Statistics of Meta-Analysis 　　　 Analysis Using R 　　　 Meta-Regression 　　　 Publication Bias 　　　 Summary of Findings 　　　 Final Comments 　　　 Bayesian Inference Introduction 　　　 Bayesian Inference 　　　 Analysis Using R 　　　 Summary of Findings 　　　 Final Comments 　　　 Principal Component Analysis Introduction 　　　 Principal Component Analysis 　　　 Analysis Using R 　　　 Summary of Findings 　　　 Final Comments Multidimensional Scaling Introduction 　　　 Multidimensional Scaling 　　　 Analysis Using R 　　　 Summary of Findings 　　　 Final Comments 　　　 Cluster Analysis Introduction 　　　 Cluster Analysis 　　　 Analysis Using R 　　　 Summary of Findings 　　　 Final Comments Bibliography Index
520			_aFeatures Presents straightforward descriptions of how to use R and interpret the results Gives an introduction to R for novices, covering basic concepts and common data manipulation techniques Shows how to obtain informative graphical output by applying the appropriate R functions Includes more examples and exercises that encourage hands-on practice with R Offers the data, R code, and lecture slides in the HSAUR3 package available from CRAN Summary Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. New to the Third Edition Three new chapters on quantile regression, missing values, and Bayesian inference Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables Additional exercises More detailed explanations of R code New section in each chapter summarizing the results of the analyses Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.
650			_aMathematical Statistics _aData processing handbook _aR computer Program Language _aR computer Programing Language
942			_cBK
999			_c102345 _d102345