Multivariate Data Analysis detailed syllabus for Computer Science & Engineering (CSE) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the CSE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Computer Science & Engineering 7th Sem scheme and its subjects, do visit CSE 7th Sem 2021 regulation scheme. For Open Elective-IV scheme and its subjects refer to CSE Open Elective-IV syllabus scheme. The detailed syllabus of multivariate data analysis is as follows.
Course Objectives:
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Unit I
INTRODUCTION 9 Uni-variate, Bi-variate and Multi-variate techniques – Classification of multivariate techniques -Guidelines for multivariate analysis and interpretation.
Unit II
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Unit III
MULTIPLE LINEAR REGRESSION ANALYSIS, FACTOR ANALYSIS 9 Multiple Linear Regression Analysis – Inferences from the estimated regression function – Validation of the model. -Approaches to factor analysis – interpretation of results.
Unit IV
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Unit V
ADVANCED MULTIVARIATE TECHNIQUES 9 Multiple Discriminant Analysis, Logistic Regression, Cluster Analysis, Conjoint Analysis, multidimensional scaling.
Course Outcomes:
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Reference Books:
- Joseph F Hair, Rolph E Anderson, Ronald L. Tatham & William C. Black, Multivariate Data Analysis, Pearson Education, New Delhi, 2005.
- Barbara G. Tabachnick, Linda S.Fidell, Using Multivariate Statistics, 6th Edition, Pearson, 2012.
- Richard A Johnson and Dean W.Wichern, Applied Multivariate Statistical Analysis, Prentice Hall, New Delhi, 2005.
- David R Anderson, Dennis J Seveency, and Thomas A Williams, Statistics for Business and Economics, Thompson, Singapore, 2002
For detailed syllabus of all the other subjects of Computer Science & Engineering 7th Sem, visit CSE 7th Sem subject syllabuses for 2021 regulation.
For all Computer Science & Engineering results, visit Anna University CSE all semester results direct link.