Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added. All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior. All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate Statistical Analysis offers the following new features: A new chapter on Variable Selection (Lasso, SCAD and Elastic Net) All exercises are supplemented by R and MATLAB code that can be found on www.quantlet.de. The practical exercises include solutions that can be found in Härdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg. Table of Contents Part I Descriptive Techniques Chapter 1 Comparison of Batches Part II Multivariate Random Variables Chapter 2 A Short Excursion into Matrix Algebra Chapter 3 Moving to Higher Dimensions Chapter 4 Multivariate Distributions Chapter 5 Theory of the Multinormal Chapter 6 Theory of Estimation Chapter 7 Hypothesis Testing Part III Multivariate Techniques Chapter 8 Regression Models Chapter 9 Variable Selection Chapter 10 Decomposition of Data Matrices by Factors Chapter 11 Principal Components Analysis Chapter 12 Factor Analysis Chapter 13 Cluster Analysis Chapter 14 Discriminant Analysis Chapter 15 Correspondence Analysis Chapter 16 Canonical Correlation Analysis Chapter 17 Multidimensional Scaling Chapter 18 Conjoint Measurement Analysis Chapter 19 Applications in Finance Chapter 20 Computationally Intensive Techniques Part IV Appendix Chapter 21 Symbols and Notations Chapter 22 Data

房屋价格分析 语境 房价受许多因素影响，包括平方英尺，材料的表面光洁度以及附近地区等。 目的是确定哪些因素对房屋的最终销售价格影响最大。 统计分析对于确定哪些因素更具影响力至关重要。 数据集 该数据集适用于爱荷华州埃姆斯市。 它是从Kaggle检索得到的，包含79列，包含1,460个观测值。

The purpose of this book is to help the climatologist understand the basic precepts of the statistician’s art and to provide some of the background needed to apply statistical methodology correctly and usefully. The book is self contained: introductory material, standard advanced techniques, and the specialized techniques used specifically by climatologists are all contained within this one source. There is a wealth of realworld examples drawn from the climate literature to demonstrate the need, power and pitfalls of statistical analysis in climate research.

多元统计分析的绝佳教材，第三版了，斯坦福大学Aderson经典之作

SARS Covid 2的全球数据分析 网络抓取工具worldosmeters_scraper.exe从worldometers.info中获取所有数据，并每天创建所有国家/地区的today_worldwide_covid19_data.csv数据库。 然后， covid19_analysis_2.2.py分析所有数据。 该脚本有两种语言，希腊语和英语。 只需输入“ GR”（希腊）或“ EN”（英语）即可。 如果您想测试脚本，只需下载covid19_analysis_2.2.exe并运行它。 today_worldwide_covid19_data.csv每天更新。 与old_version的区别在于，现在您可以从.csv文件中的224检查每个国家或地区的统计信息而且您只需下载一次.exe，而不是每天都要下载的旧版本！ 输出： 资料来源

《Applied Multivariate Statistical Analysis》pdf, Wolfgang, 4th edition, 英文版

Perfected over three editions and more than forty years, this field- and classroom-tested reference: 　　* Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. 　　* Treats all the basic and important topics in multivariate statistics. 　　* Adds two new chapters, along with a number of new sections. 　　* Provides the most methodical, up-to-date information on MV statistics available.　　

这本书出自 Richard A. Johnson (Author), Dean W. Wichern (Author) 两位著名的教授，是这个领域比较著名的数，在工业工程，经济管理，工程科技等涉及多变量的领域应用广泛。仅仅用作学习目的，阅后请删除。

许多人觉得统计分析令人费解。为什么? 因为它需要新的思维方式。你又如何理解这些新的思维方式呢? 为了正确理解统计分析，你需要理解它的一些关键基础。阅读教科书是行不通的，因为教科书没有关注基础，而且它们涵盖了太多的内容和细节，读者必然会只见树木不见森林。我有很多方法来补救这种状况。我做的第一件事是关注一个每个人都应该熟悉的应用领域。第二，我关注最直接的调研问题和回答——你同意还是不同意?你赞成还是不赞成?我所做的第三件事是关注那些对于理解统计分析的本质和对结果的解释至关重要的基础，无论是民意调研结果还是药物试验结果。第四，我用了很多插图。即使你以前学过统计学课程，即使你知道执行统计分析的机制，你也会从这些基础中受益。

Statistical Analysis Microsoft Excel 2016 英文无水印原版pdf pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书