Course Status : | Ongoing |
Course Type : | Core |
Language for course content : | English |
Duration : | 12 weeks |
Category : |
|
Credit Points : | 5 |
Level : | Undergraduate |
Start Date : | 15 Jul 2024 |
End Date : | 31 Oct 2024 |
Enrollment Ends : | 31 Aug 2024 |
Exam Date : | 07 Dec 2024 IST |
Exam Shift : | First |
Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.
Week 1 :
Module 1: Nature and Scope of Econometrics
Module 2: Models, Aims and methodology of Econometrics
Module 3: Limitations of Econometrics
Module 4: Basic Statistical concepts
Interaction 1; Assignment 1.
Week 2 :
Module 5: Estimate and estimator, Point vs. Interval
estimation, Properties of estimators
Module 6: Probability distributions
Module 7: Normal distribution
Module 8: Uses of probability distributions in econometrics
Assignment 2.
Week 3 :
Module 9: Hypothesis-I
Module 10: Hypothesis-II
Module 11: Type I and Type II errors
Module 12: Power of a test
Interaction 2; Assignment 3.
Week 4 :
Module 13: Tests for comparing parameters from two samples
Module 14: Simple
linear regression model
Module 15: Stochastic
specification
Module 16: Significance of the error term
Assignment 4.
Week 5 :
Module 17: Ordinary
Least Squares
Module 18:
Assumptions of classical linear regression model
Module 19: BLUE, The
Gauss Markov Theorem
Module 20: Multiple linear regression model-I
Interaction 2, Assignment 5
Week 6 :
Module 21: Multiple linear regression model-II
Module 22: Dummy variable; Problem associated with dummy
variable-dummy variable trap
Module 23: Goodness of fit
Module 24: Adjusted R square
Assignment 6.
Week 7 :
Module 25: Forecasting
Module 26: Violations of classical assumptions
Module 27: Heteroscedasticity, Problem and consequences
Assignment 7
Week 8 :
Module 28: Heteroscedasticity- detection, alternative
methods of estimation.
Module 29: Autocorrelation, sources and consequences
Module 30: Durbin Watson d test
Interaction 3
Assignment 8.
Week 9 :
Module 31: Autocorrelation-remedial measures
Module 32: Multicollinearity-Problem and consequences
Module 33: Detection of multicollinearity
Assignment 9
Week 10 :
Module 34: Multicollinearity- remedial measures
Module 35: Multicollinearity- remedial measures (contd.)
Module 36: Specification bias
Assignment 10, Interaction 4.
Week 11 :
Module 37: Omission of relevant variables
Module 38: Inclusion of irrelevant variables
Module 39: Test for specification bias
Assignment 11.
Week 12 :
Module 40: Errors in variable
Interaction 5, Assignment 12
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