**Data Analysis and Visualization in R**, and kindly contributed to R-bloggers)

PACKT marketing guys again contact me to review their new book *Mastering Scientific Computing with R*. The book 432 pages (including covers) book is consist of 10 chapters which starts from basic R and ends with advanced data management. However, between the basic R and advanced data management chapters were topics on linear and non linear models, nonparametric techniques, linear and matrix algebra, principal component analysis, and structural equation modeling and confirmatory factor analysis

Aside from code samples (even for R beginners) which include additional comments, there is also an online tutorial on Structural Equation Modeling included in the book webpage which make the book content easier to learn. In addition, the book also extends discussion beyond the methodological aspect of using R in scientific computing by providing technical and practical approach in some of the methodologies (e.g. “choosing the number of components to retain in Principal Component Analysis”, “Rasch analysis using linear algebra and a

paired comparisons matrix”, “Exploratory factor analysis and reflective

constructs”).

Highly recommended book!

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