Syllabus of National Institute of Technology - Tiruchirappalli (NIT-T) MBA - MB775 Data Analytics I

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. Multiple Regression: Assumptions for General Linear Regression Model, Ordinary Least Square (OLS) Approach – measures of fit, statistical inferences – Hypothesis testing and interval estimation – Data cleaning – Outliers and influential observations. Retaining of predictors – Forward, backward, stepwise, sequential and all possible subsets. Dummy regressions and conjoint analysis, multi collinearity. Discriminant Analysis – I : Introduction, The Two Group problem – Variable contribution – The case of discrete – Variables – logistic regression, Error rate estimation. Discriminant Analysis – II: The K groups problem, Error rate estimate in multiple groups, Interpretation of multiple discriminant analysis solution. Factor Analysis : The basic model, Extraction of factors – Principal factor – maximum likelihood method, factor rotation – orthogonal, oblique rotations, factor score, interpretations of factor analysis solutions.

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.