In: Statistics and Probability
The table below shows data collected on the vessel calls for a port in Ghana, from 2007-2016 to study the relationship between the number of Commercial Vessels (C.V.) and Offshore Vessels (O. V.). Year 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 C. V. (X) 527 486 481 558 623 611 606 543 615 673 O. V. (Y ) 67 129 475 719 1175 1053 758 844 910 928 Assuming a linear regression model E(Y |X = x) = α + β(x − x¯): a. Fit a regression model of the number of offshore vessels on commercial vessels, and give practical interpretation of the regression parameter estimates. [10 Marks] b. Construct a 95% confidence and prediction intervals for the number of offshore vessels corresponding to 742 commercial vessels.
Create a table of all summations as below
n | Commerical Vessels (X) | Offshore Vessels (Y) | X^2 | Y^2 | XY |
1 | 527 | 67 | 277729 | 4489 | 35309 |
2 | 486 | 129 | 236196 | 16641 | 62694 |
3 | 481 | 475 | 231361 | 225625 | 228475 |
4 | 558 | 719 | 311364 | 516961 | 401202 |
5 | 623 | 1175 | 388129 | 1380625 | 732025 |
6 | 611 | 1053 | 373321 | 1108809 | 643383 |
7 | 606 | 758 | 367236 | 574564 | 459348 |
8 | 543 | 844 | 294849 | 712336 | 458292 |
9 | 615 | 910 | 378225 | 828100 | 559650 |
10 | 673 | 928 | 452929 | 861184 | 624544 |
SUM → | 5723 | 7058 | 3311339 | 6229334 | 4204922 |
Tabulate the values using regression parameters as below on excel
Regression Parameters | Commerical Vessels (X) | Offshore Vessels (Y) | Estimated Values | SSE | |
a | -1922.409 | 527 | 67 | 497.7659852 | 185559.334 |
b | 4.59236236 | 486 | 129 | 309.4791286 | 32572.71586 |
481 | 475 | 286.5173168 | 35525.72186 | ||
558 | 719 | 640.1292183 | 6220.600207 | ||
623 | 1175 | 938.6327715 | 55869.46671 | ||
611 | 1053 | 883.5244232 | 28721.97113 | ||
606 | 758 | 860.5626114 | 10519.08926 | ||
543 | 844 | 571.2437829 | 74395.95394 | ||
615 | 910 | 901.8938726 | 65.70930079 | ||
673 | 928 | 1168.250889 | 57720.48983 | ||
SUM → | 487171.0521 |