Fundamentals of Econometrics
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Fundamentals of Data Mining SOLVED PAPERS AND GUESS
Product Details: M D U UNIVERSITY Fundamentals of Data Mining
Format: BOOK
Pub. Date: NEW EDITION APPLICABLE FOR Current EXAM
Publisher: MEHTA SOLUTIONS
Edition Description: 2021-22
RATING OF BOOK: EXCELLENT
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Fundamentals of Data Mining
UNIT-I
Nature, scope and methodology of econometrics; Simple Linear Regression Model: Assumptions, Procedures and
properties of OLS estimator, Co-efficient of determination, Tests of significance, Maximum Likelihood Method
UNIT-II
Multiple Linear Regression Analysis: Method of least squares, Properties of OLS estimator, Test of significance
of regression co-efficient, R2 and adjusted R2; Econometric Problems: Multicollinearity, Autocorrelation and
Hetroscedasticity.
UNIT-III
Dummy variables-Nature and uses, Regression on dummy variables, Regression on Dummy Dependent VariableThe basic idea of the Linear Probability Model (LPM), Probit and Logit Models. Dynamic Econometric Models:
Koyck distributed lag model, the adaptive expectation model, and the partial adjustment model.
UNIT-IV
Simultaneous Equation Models: Structural, Reduced and final forms, Identification-Order and rank conditions,
Methods for estimating the simultaneous models-Basic idea of Indirect Least Square (ILS) and Two Stage Least
Square (2SLS) methods. Seemingly Unrelated Regressions (SUR), SUR versus OLS.
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