Sugnet Gardner Lubbe – författare

Biplots are a graphical method for simultaneously displaying two kinds of information; typically, the variables and sample units described by a multivariate data matrix or the items labelling the rows and columns of a two-way table. This book aims to popularize what is now seen to be a useful and reliable method for the visualization of multidimensional data associated with, for example, principal component analysis, canonical variate analysis, multidimensional scaling, multiplicative interaction and various types of correspondence analysis.

Understanding Biplots:

• Introduces theory and techniques which can be applied to problems from a variety of areas, including ecology, biostatistics, finance, demography and other social sciences.

• Provides novel techniques for the visualization of multidimensional data and includes data mining techniques.

• Uses applications from many fields including finance, biostatistics, ecology, demography.

• Looks at dealing with large data sets as well as smaller ones.

• Includes colour images, illustrating the graphical capabilities of the methods.

• Is supported by a Website featuring R code and datasets.

Researchers, practitioners and postgraduate students of statistics and the applied sciences will find this book a useful introduction to the possibilities of presenting data in informative ways.

Biplots are a graphical method for simultaneously displaying two kinds of information; typically, the variables and sample units described by a multivariate data matrix or the items labelling the rows and columns of a two-way table. This book aims to popularize what is now seen to be a useful and reliable method for the visualization of multidimensional data associated with, for example, principal component analysis, canonical variate analysis, multidimensional scaling, multiplicative interaction and various types of correspondence analysis.

Understanding Biplots:

• Introduces theory and techniques which can be applied to problems from a variety of areas, including ecology, biostatistics, finance, demography and other social sciences.

• Provides novel techniques for the visualization of multidimensional data and includes data mining techniques.

• Uses applications from many fields including finance, biostatistics, ecology, demography.

• Looks at dealing with large data sets as well as smaller ones.

• Includes colour images, illustrating the graphical capabilities of the methods.

• Is supported by a Website featuring R code and datasets.

Researchers, practitioners and postgraduate students of statistics and the applied sciences will find this book a useful introduction to the possibilities of presenting data in informative ways.