Fundamentals of Econometrics   SOLVED PAPERS AND GUESS

Product Details: Rohtak   UNIVERSITY Fundamentals of Econometrics

Format: BOOK

Pub. Date: NEW EDITION APPLICABLE FOR Current EXAM

Publisher: MEHTA SOLUTIONS

Edition Description: 2021-22

RATING OF BOOK: EXCELLENT

ABOUT THE BOOK

FROM THE PUBLISHER

If you find yourself getting fed up and frustrated with other Rohtak   UNIVERSITY book solutions now mehta solutions brings top solutions for Rohtak   UNIVERSITY Fundamentals of Data Mining  REPORT book contains previous year solved papers plus faculty important questions and answers specially for Rohtak   UNIVERSITY .questions and answers are specially design specially for Rohtak   UNIVERSITY students .

Please note: All products sold on mbabooksindia.com are brand new and 100% genuine

Case studies solved
New addition fully solved
last 5 years solved papers with current year plus guess

PH: 07011511310 , 09899296811 FOR ANY problem

FULLY SOLVED BOOK LASY 5 YEARS PAPERS SOLVED PLUS GUESS

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.