Total No. of Questions 10] [Total No. of Pages 01
M.Sc. DEGREE EXAMINATION, MAY 2018
Second Year
STATISTICS
Econometrics
Time 3 Hours Maximum Marks :70
Answer any five questions.
All questions carry equal marks.
Q1) Define simple Regression Analysis? Explain its practical applications.
Obtain the least square estimator of β in the simple linear model Y Xβ +Ε
and show that the least square estimator is BLUE.
Q2) Write the procedure of log linear regression model.
Develop a test statistic for testing the significance of the slop parameter.
Q3) State and prove Gauss Markov theorem.
Explain the general linear model. Obtain the OLS estimators of the
parameters in the model.
Q4) What is multiple correlation co-efficient Explain its role in regression
model.
Define R and R-2. Explain the importance of these in the model.
Q5) Explain the role of dummy variables in regression models.
Develop a test procedure for testing the general linear hypothesis.
Q6) Explain MWD test for choosing between Linear and Log-Linear models.
Explain chow-test procedure.
Q7) Explain any two tests for the detection of heteroscedasticity.
What are the assumptions of generalized least squares method.
Q8) What is the problem of heteroscedasticity? How do you resolve
heteroscedasticity.
What is multicollinearity? State different solutions for multi collinearity.
Q9) Explain about PROBIT model. How do you estimate the model.
Explain Auto correlation? Explain Dubin-Watson test.
Q10)a) Explain about LOGIT Model in brief.
Write the structure of linear probability model. Explain its features.