Week 1:
Module 1: Nature and Scope of Econometrics
Module 2: Models, Aims and Methodology of Econometrics
Module 3: Basic Statistical Concepts
Module 4: Estimate and Estimator, Point vs. Interval Estimation
Week 2:
Module 5: Properties of Estimators
Module 6: Probability Distributions
Module 7: Uses of Probability Distributions in Econometrics
Week 3:
Module 8: Hypothesis I
Module 9: Hypothesis II
Module 10: Type I and Type II Errors
Week 4:
Module 11: Power of a Test
Module 12: Tests for Comparing Parameters from two Samples
Week 5:
Module 13: Simple Linear Regression Model
Module 14: Stochastic Specification
Week 6:
Module 15: Ordinary Least Squares
Module 16: BLUE, The Gauss Markov Theorem, Goodness of fit
Module 17: k-variable linear regression model, Dummy variable
Week 7:
Module 18: Violations of Classical Assumptions
Module 19: Heteroscedasticity, Problem and Consequences
Week 8:
Module 20: Heteroscedasticity- Detection, Alternative Methods of Estimation.
Module 21: Autocorrelation, Sources and Consequences
Module 22: Tests of Autocorrelation
Week 9:
Module 23: Autocorrelation-Remedial Measures
Module 24: Multicollinearity-Problem and Consequences
Module 25: Detection of multicollinearity
Week 10:
Module 26: Multicollinearity- Remedial Measures
Module 27: Multicollinearity- Remedial Measures (contd.)
Module 28: Specification bias
Week 11:
Module 29: Omission of Relevant Variables
Module 30: Inclusion of Irrelevant Variables
Module 31: Test for Specification Bias
Week 12:
Module 32: Errors in Variable
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