Advanced Business Research — DU B.Com. (Hons.) Previous Year Question Papers

A university is conducting a study to examine.the factors affecting students' final examination scores. The researcher believes that study hours, attendance percentage, and internet usage for academic purposes influence student performance. The following multiple regression model is est`imat.ed: Variable Coefficient Standard Error t-Statistic p-value htercept 28.40 6.10 4.66 0.000 Study Hours (X1) 5.20 1.10 4.73 0.000 Internet Usage (X3) 0.90 0.50 1.80 0.082 y= Final Exam score (out ofl00) Xi= Average study Hours per Day X2= Attendance percentage X3= Internet usage for Academic work (hours per week) Additional Information : Prob(F-statistic) = 0.0000 Number of observations = 40 Questions a) b) Write the estimated regression equation from the above ouq]ut. htelpret the coefficient of study Hours and Attendance percentage.. c) est whether Attendance Percentage significantly. affects exam scores at 5°/o level of significance. d) Explain the meaning ofjz2and Adjusted R2in the context of this model. e) What does the F-statistic indicate about the overall significance of the regression model? 1) Is Internet Usage statistically significant at 5% level? Explain with reasons. Answer the following questions related to Multiple Regression Analysis and its assumptions: Linear Regression? Discuss its applications in economics, management, and business research. b) Discuss the assumptions of the Classical Linear Regression Model (CLRM) in detail. Why are these assumptions important for obtaining reliable regression results? c) Explain the problem of Autocorrelation in regression analysis. Discuss its causes, consequences, and methods of detection. d) What is the difference between Homoskedasticity and Heteroskedasticity? Explain the impact of heteroskedasticity on Ordinary Least Squares (OLS) estimates. e) Explain the significance of the following in regression analysis: a) F-test c) p-value f) What is the Variance Inflation Factor (VIF)? How does it help in detecting multicollinearity in a regression model? Arrera Multiple Regression Model C T Variable / ER Coefficient Standard Error t-Statistic p-value Study Hours (XI) 5.20 1.10 4.73 0.000 Internet Usage (X3) 0.90 0.50 1.80 0.082 8. Prob(F-statistic) = 0.0000 4. Number of observations = 40 3. BURIAT Output F 3EA Regression Equation faragl Be Study Hours Aº Attendance Percentage cofficiens 3. 5% significance level YR vİa ф\fGy fO Attendance Percentage Ran 3іФі Ф]. 4А F-statistic regression model overall significance 8e ФЧ İnternet Usage, 5% significance level 8 statist Multiple Regression alysis (Multiple Regression Analysis 7 308 | 7Ş| E Simple Linear Regression # (89 Classical Linear Regression Model (LN And (a) Variance Inflation Factor (VIF) 441 0? 4ğ Regression Model # Multicollinearity i ala