stats hw3 - 6. 14.55 [This question is worked out in a team...

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6. 14.55 [This question is worked out in a team by Liwei He and Sheng Kang] a) The scatterplots of the variables are shown in the graph below. We can see that variable 3 and variable 4 (tank vapor pressure and gas vapor pressure) has a very strong linear relationship. Variable 1 (tank temperature) shows clustered relationship with other variables. Looking at the last row of the plots, we can see that variable 2, 3 and 4 will be more important in the model than variable 1, as they have stronger relationship with variable 5 (emitted hydrocarbon). From the plots on the diagonal, it can be seen the variables do not spread out well, therefore transformation may be helpful. Also, there appears to have some outliers as shown in the plots of column 1 and 2. b) First regress emitted hydrocarbon against all the other 4 variables, the regression results are: Summary of Fit Rsquare 0.8754 Rsquare Adj 0.8691 Mean Square Error 7.7276
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β standard error t p-value constant -0.06433 1.363096421 -0.04719 0.962479 TankTemp -0.0821 0.063584053 -1.29117 0.2003636 GasTemp 0.209344 0.061409829 3.40896
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This note was uploaded on 04/07/2010 for the course SLOAN 15.077 taught by Professor Roy during the Spring '10 term at MIT.

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stats hw3 - 6. 14.55 [This question is worked out in a team...

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