# Multivariate Statistics

## Exercises and Solutions

• Wolfgang Karl Härdle
• Zdeněk Hlávka
Textbook

1. Front Matter
Pages i-xxiv
2. ### Descriptive Techniques

1. Front Matter
Pages 1-1
2. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 3-18
3. ### Multivariate Random Variables

1. Front Matter
Pages 19-19
2. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 21-26
3. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 27-42
4. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 43-70
5. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 71-88
6. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 89-101
7. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 103-137
4. ### Multivariate Techniques

1. Front Matter
Pages 139-139
2. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 141-156
3. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 157-165
4. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 167-181
5. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 183-203
6. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 205-224
7. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 225-244
8. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 245-258
9. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 259-280
10. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 281-287
11. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 289-299
12. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 301-308
13. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 309-317
14. Wolfgang Karl Härdle, Zdeněk Hlávka
Pages 319-341
5. Back Matter
Pages 343-362

### Introduction

The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether more than 250 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R language. All R codes and data sets may be downloaded via the quantlet download center  www.quantlet.org or via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.

### Keywords

data analysis factor analysis factor model high dimensional data analysis multivariate distribution multivariate statistics principal component quantlets regression models

#### Authors and affiliations

• Wolfgang Karl Härdle
• 1
• Zdeněk Hlávka
• 2
1. 1.C.A.S.E. Centre f. Appl. Stat. & Econ. School of Business and EconomicsHumboldt-Universität zu BerlinBerlinGermany
2. 2.Faculty of Mathematics and Physics, Department of StatisticsCharles University in PraguePragueCzech Republic