数据可视化相关书籍
本资源包含两本:python数据可视化编程实战中文版和数据可视化手册英文版。
1:Learning Pentaho CTools(PACKT,2016).pdf 2:Pentaho Data Integration Beginner's Guide, Second Edition.pdf 3:Packt.Pentaho for Big Data Analytics.2013.pdf 4:pentaho kettle solutions.pdf 5:[Packt Publishing] Pentaho 5.0 Reporting by Example Beginner's Guide.pdf 6:Pentaho+Data+Integration 这次是合集。
分享创造价值,开源促进创新。 作 者:赵晓群 著 丛 书 名:信息与通信工程研究生规划教材 出 版 社:华中科技大学出版社 ISBN:9787560944579 出版时间:2008-08-01 版 次:1 页 数:300 装 帧:平装 开 本:16开
分享产生价值! A valuable new edition of a standard reference "A 'must-have' book for anyone expecting to do research and/or applications in categorical data analysis." –Statistics in Medicine on Categorical Data Analysis, First Edition The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. Responding to new developments in the field as well as to the needs of a new generation of professionals and students, this new edition of the classic Categorical Data Analysis offers a comprehensive introduction to the most important methods for categorical data analysis. Designed for statisticians and biostatisticians as well as scientists and graduate students practicing statistics, Categorical Data Analysis, Second Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial regression for discrete data with normal regression for continuous data. Adding to the value in the new edition is coverage of: Three new chapters on methods for repeated measurement and other forms of clustered categorical data, including marginal models and associated generalized estimating equations (GEE) methods, and mixed models with random effects Stronger emphasis on logistic regression modeling of binary and multicategory data An appendix showing the use of SAS for conducting nearly all analyses in the book Prescriptions for how ordinal variables should be treated differently than nominal variables Discussion of exact small-sample procedures More than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercises An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.