Multivariate analysis techniques are popular because they enable organizations to create knowledge and thereby improve their decision making. Multivariate analysis refers to all statistical techniques that simultaneously analyze multiple measurements on individuals or objects under investigation. Thus, any simultaneous analysis of more than two variables can be loosely considered multivariat…
The statistical science has seen new paradigms and more complex and richer data sets. These include data on human genomics, social networks, huge climate and weather data, and, of course, high frequency financial and economic data.
The fourth edition of this book on Applied Multivariate Statistical Analysis offers a new sub-chapter on Variable Selection by using least absolute shrinkage and selection operator (LASSO) and its general form the so-called Elastic Net.
The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features. 1. A new Chapter 8 on Regression Models has been added. 2. Almost all numerical examples have been reproduced in MATLAB or R. The chapter on regression models focuses on a core business of multivariate statistical analysis. This contribution has not been subject of a prominent dis…
For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of th…
his is the fourth edition of the book Multivariate Statistical Methods: a Primer. The contents are similar to what was in the third edition of the book, with the main difference being the introduction of R code to do all of the analyses in the fourth edition. The version of R used for running the R-scripts (and the corresponding packages) is R 3.3.1. Also, the results obtained with the R c…
Buku pemodelan persamaan struktural (SEM) dari Barbara Byrne ini meninjau konsep dasar dan aplikasi SEM menggunakan Mplus Versi 5 & 6. Penulis meninjau aplikasi SEM berdasarkan data aktual yang diambil dari penelitiannya sendiri. Menggunakan bahasa non-matematika, ini ditulis untuk pengguna SEM pemula. Dengan setiap bab aplikasi, penulis "menuntun" pembaca melalui semua langkah yang terlibat da…
Kemajuan teknologi informasi memungkinkan penggunaan metode statistic multivariate untuk mengolah data yang kompleks dan tidak dapat dilakukan oleh metode statistik’klasik’seperti uji t,anova dan lainnya. Buku ini merupakan revisi dari buku latihan statistic multivariate,untuk memudahkan pemahaman materi,pada setiap topic disertai contoh kasus,cara mengolahnya dengan metode multivariate te…