Introduction to Multivariate Analysis: Linear and Nonlinear Modeling

Author:   Sadanori Konishi (Chuo University, Tokyo, Japan)
Publisher:   Taylor & Francis Inc
Volume:   134
ISBN:  

9781466567283


Pages:   338
Publication Date:   06 June 2014
Format:   Hardback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Introduction to Multivariate Analysis: Linear and Nonlinear Modeling


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Author:   Sadanori Konishi (Chuo University, Tokyo, Japan)
Publisher:   Taylor & Francis Inc
Imprint:   CRC Press Inc
Volume:   134
Dimensions:   Width: 15.20cm , Height: 2.30cm , Length: 22.90cm
Weight:   0.790kg
ISBN:  

9781466567283


ISBN 10:   1466567287
Pages:   338
Publication Date:   06 June 2014
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Reviews

The presentation is always clear and several examples and figures facilitate an easy understanding of all the techniques. The book can be used as a textbook in advanced undergraduate courses in multivariate analysis, and can represent a valuable reference manual for biologists and engineers working with multivariate datasets. -Fabio Rapallo, Zentralblatt MATH 1296


The presentation is always clear and several examples and figures facilitate an easy understanding of all the techniques. The book can be used as a textbook in advanced undergraduate courses in multivariate analysis, and can represent a valuable reference manual for biologists and engineers working with multivariate datasets. -Fabio Rapallo, Zentralblatt MATH 1296 This is an excellent textbook for upper-class undergraduate and graduate level students. The prerequisites are an introductory probability and statistics and linear algebra courses. To aid the student in the understanding and use of vector and matrix notations, and to emphasize that importance, the author appropriately uses the algebraic notation accompanied by the vector and matrix notations when needed; additionally, the accompanying geometrical interpretation are presented in clear diagrams. The writing style is crisp and clear. A pleasant format that the author used is to summarily review relevant topics in a narrative style to pave the way into a new topic. The textbook is accessible to students and researchers in the social sciences, econometrics, biomedical, computer and data science fields. This is the kind of textbook that a student or professional researcher will consult many times. -Stephen Hyatt, International Technological University


The presentation is always clear and several examples and figures facilitate an easy understanding of all the techniques. The book can be used as a textbook in advanced undergraduate courses in multivariate analysis, and can represent a valuable reference manual for biologists and engineers working with multivariate datasets. -Fabio Rapallo, Zentralblatt MATH 1296 This is an excellent textbook for upper-class undergraduate and graduate level students. The prerequisites are an introductory probability and statistics and linear algebra courses. To aid the student in the understanding and use of vector and matrix notations, and to emphasize that importance, the author appropriately uses the algebraic notation accompanied by the vector and matrix notations when needed; additionally, the accompanying geometrical interpretation are presented in clear diagrams. The writing style is crisp and clear. A pleasant format that the author used is to summarily review relevant topics in a narrative style to pave the way into a new topic. The textbook is accessible to students and researchers in the social sciences, econometrics, biomedical, computer and data science fields. This is the kind of textbook that a student or professional researcher will consult many times. -Stephen Hyatt, International Technological University The presentation is always clear and several examples and figures facilitate an easy understanding of all the techniques. The book can be used as a textbook in advanced undergraduate courses in multivariate analysis, and can represent a valuable reference manual for biologists and engineers working with multivariate datasets. -Fabio Rapallo, Zentralblatt MATH 1296 This is an excellent textbook for upper-class undergraduate and graduate level students. The prerequisites are an introductory probability and statistics and linear algebra courses. To aid the student in the understanding and use of vector and matrix notations, and to emphasize that importance, the author appropriately uses the algebraic notation accompanied by the vector and matrix notations when needed; additionally, the accompanying geometrical interpretation are presented in clear diagrams. The writing style is crisp and clear. A pleasant format that the author used is to summarily review relevant topics in a narrative style to pave the way into a new topic. The textbook is accessible to students and researchers in the social sciences, econometrics, biomedical, computer and data science fields. This is the kind of textbook that a student or professional researcher will consult many times. -Stephen Hyatt, International Technological University


The presentation is always clear and several examples and figures facilitate an easy understanding of all the techniques. The book can be used as a textbook in advanced undergraduate courses in multivariate analysis, and can represent a valuable reference manual for biologists and engineers working with multivariate datasets. -Fabio Rapallo, Zentralblatt MATH 1296 This is an excellent textbook for upper-class undergraduate and graduate level students.ã The prerequisites are an introductory probability and statistics and linear algebra courses.ã To aid the student in the understanding and use of vector and matrix notations, and to emphasize that importance, the author appropriately uses the algebraic notation accompanied by the vector and matrix notations when needed; additionally, the accompanying geometrical interpretation are presented in clear diagrams.ã The writing style is crisp and clear.ã A pleasant format that the author used is to summarily review relevant topics in a narrative style to pave the way into a new topic.ã The textbook is accessible to students and researchers in the social sciences, econometrics, biomedical, computer and data science fields.ã This is the kind of textbook that a student or professional researcher will consult many times. -Stephen Hyatt, International Technological University ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã ã


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