The course will enable the students to
1 To acquaint the students with the use of software EViews to detect the violation of assumptions of the regression model.
2.To describe the use of EViews for estimating models with dummy independent variables.
Course Outcomes (COs).
Course Outcomes (at course level) | Learning and teaching strategies | Assessment Strategies |
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On completion of this course, the students will: CO206. Demonstrate the various methods of detecting the problems of multicollinearity, heteroscedasticity, autocorrelation and specification error using EViews. CO207. Estimate and interpret models comprising of dummy variables. CO208. Learn how to use statistical software , like EViews, in controlling the problems related with violation of OLS assumptions. CO209. Learn how to use the qualitative values in cause-effect related phenomenon. CO210. Be trained about practical knowledge related with interpretation of empirical results for policy formulation | Approach in teaching. Interactive Lectures, Discussion and Demonstration.
Learning activities for the students. Practice modules and Assignments. | Practical File Preparation, Assignments, Semester end examinations. |
Unit I 9 hrs
Multicollinearity Detection of the problem of multicollinearity.
Heteroscedasticity Detection of the problem of heteroscedasticity.
Serial correlation Detection of the problem of serial correlation
Specification error Omitted variable and redundant variable tests.
Specification error Omitted variable and redundant variable tests.
Qualitative (dummy) independent variables Illustration of the uses of dummy variables.
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