M.B.A. DEGREE EXAMINATION, APRIL 2018
Third Semester
Business Analytics
MULTIVARIATE DATA ANALYSIS-I
(2016 Onwards)
Time 3 Hours Maximum 75 Marks
Part A (10 X 2 20)
Answer all questions.
1. What is multivariate analysis?
2. Define correlation analysis.
3. What are dummy variables?
4. What are non-metric data? Give an example.
5. Define a factor.
6. Illustrate H0 and H1 of factor analysis.
7. What do you understand by regression analysis?
8. Differentiate simple and multiple regressions.
9. What is discriminate analysis?
10. Write down the hypothesis of MANOVA.
Sub. Code
32
CP-8790
2
sp2
Part B X 5 25)
Answer all questions.
11. Discuss about classification of multivariate
techniques.
Or
Explain guideline for multivariate analyses and its
interpretation.
12. Discuss about graphical examination of data.
Or
How will you test the assumptions of multivariate
analysis? Explain.
13. Explain the following: Eigen value Factor
loading
Or
Describe about factor analysis decision process.
14. Elucidate decision process for multiple regression
analysis.
Or
Consider the following set of points:

Find the least square regression line for the
given data points.
Plot the given points and the regression line
15. Illustrate decision process for discriminate analysis.
Or
Explain about binary dependent variable in and
dichotomous variable in logistic regression.
Part C X 10 30)
Answer all questions.
16. Suggest a structured approach to multivariate
model building with example.
Or
Discuss in detail about managerial overview of
factor analysis and its result.
17. Find regression equation for the following:
Y X1 X2
Y 29.75 139.5 90.25
X1 0.77 1091.8 515.5
X2 0.72 0.68 521.75
Or
How does regression analysis help in managerial
decision making? Explain.
18. Give an illustrative example of logistic regression.
Or
Explain in detail about analogy of regression and
MANOVA.
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