Estimate the Regression Line of Sale on Price and Interpret the Results – Management Assignment Help

Assignment Task:

Task:

Individual Assignment

1. The following data refers to the price of a good ‘P’ and the quantity of the good supplied, ‘S’.

P	2	7	5	1	4	8	2	8
S	15	41	32	9	28	43	17	40

1. Estimate the linear regression line
2. Estimate the standard errors of
3. Test the hypothesis that price influences supply
4. The following results have been obtained from a simple of 11 observations on the values of sales (Y) of a firm and the corresponding prices (X).

1. Estimate the regression line of sale on price and interpret the results
2. What is the part of the variation in sales which is not explained by the regression line?  
3. Estimate the price elasticity of sales.

where C=Consumption,           Y_d=disposable income, and numbers in the parenthesis are the ‘t-ratios’

1. Test the significant of Yd statistically using t-ratios
2. Determine the estimated standard deviations of the parameter estimates  
3.  The model Y_i=a +b1X_1i +b2X_2i +b3X_3i +U_iis to be estimated from a sample of 20 observations. Using the information below obtain the OLS estimate of the parameters of the above model.

, , and

Where and

5. Discuss the nature, causes, consequences and remedies of each of the following problems we might encounter in regression analysis.

1. Muticollinearity
2. Hetroscedasticity
3. Autocorrelation
4. Use the data file wage to work on using STATA and answer the following questions

1. Examine the data
2. Carry out remedial measure(s) if there is any problem with data
3. Regress HRS on RATE, ERSP, ERNO, NEIN, AGE and DEP
4. Conduct model specification tests using linktest and ovtest commands of STATA, and interpret the result
5. Perform multicollinearity test
6. Perform hetroscedasticity test
7. Comment on the explanatory power and adequacy of the model
8. Interpret the regression coefficients

6. Use the data file EARNINGS and, using STATA for analysis, carry out the following tasks.

1. Perform a regression of EARNINGS on S where EARNINGS represents Current hourly earnings in $ and S represents education (highest grade completed) in number of years of schooling of the respondent. Interpret the regression results
2. Comment on the value of R²
3. Perform a test on the coefficients of regression. Explain the implications of the result of the test. Calculate a 95% confidence interval for the slope coefficient
4. Perform an F test for the goodness of fit and comment on the result
5. Regress S on ASVAC and SM where ASVAC is a composite measure of numerical and verbal ability of the respondent and SM is the years of schooling of the respondent’s mother. Repeat the regression using SF, the years of schooling of the father, instead of SM, and again including both as regressors. Do your regression result support the view that if you educate a male, you educate an individual, while if you educate a female, you educate a nation?
6. Regress EARNINGS on S and EXP (total out-of-school work experience in years), interpret the results and perform t tests