Syllabus of National Institute of Technology - Tiruchirappalli (NIT-T) MBA - MB776 Data Analytics II

The course is application based. SPSS or SAS package will be used for applications and analysis part. The weightage for theory is 50% and 50% for exercises through SPSS or SAS exercises. Principal component Analysis : Extracting Principal components , The geometry of principal components, deciding on how many components to retain, test of significance, component scores. Canonical Correlation Analysis : Establishment of canonical variables, establishment of canonical loading and its interpretation, Deriving cross loading and reduntancy co-efficient and their interpretation. Multidimensional scaling: Introduction, Proximities, and Data collection, spatial map-metric, nonmetric data, joint space analysis. Naming and intrepreting the dimension using canonoical correlation, attribute based perceptual mapping using factor analysis, spatial map using preference data through internal analysis and external analysis. Cluster Analysis: Similarity measures, clustering techniques – hierarchical and partitioning methods, graphical methods, assessing cluster solutions, implementation.

Books:

1. Damodar, N. Gujarathi, ' Basic Econometric', Tata McGraw Hill, 4 ed. 2004.

2. Naresh K Malhotra, 'Marketing Research', Pearson Prentice Hall, 4 ed. 2006.