From:	CSVAX::GATICA       "Jorge E. Gatica / Chemical Engineering Dept." 14-MAY-1993 15:07:02.22
To:	@ESC350_50
CC:	
Subj:	Data for extra credit - Computer Project #2


Computer Project #2 : extra credit data

The following data set is proposed to be
modelled through a linear model. Three 
possible models have been proposed :

	i)   y = a_1 + a_2 * sqrt(x)

	ii)  y = a_1 + a_2 * exp(x)

	iii) y = a_1 + a_2 * ln(1+x)

Using your "multi-parametric linear regression" 
program, which model would you recommend ? 
Report your regression results and explain 
your recommendation.


----- cut here ------------
          51
  0.0000000E+00   1.002908    
   1.000000      0.8896702    
   2.000000      0.8362570    
   3.000000      0.7838290    
   4.000000      0.7515407    
   5.000000      0.7174740    
   6.000000      0.6936612    
   7.000000      0.6756517    
   8.000000      0.6398361    
   9.000000      0.6202090    
   10.00000      0.5847427    
   11.00000      0.5854257    
   12.00000      0.5772498    
   13.00000      0.5544594    
   14.00000      0.5331414    
   15.00000      0.5144271    
   16.00000      0.4977528    
   17.00000      0.4813687    
   18.00000      0.4661770    
   19.00000      0.4548341    
   20.00000      0.4366497    
   21.00000      0.4308162    
   22.00000      0.4186812    
   23.00000      0.3991024    
   24.00000      0.3892497    
   25.00000      0.3752671    
   26.00000      0.3625365    
   27.00000      0.3526688    
   28.00000      0.3341645    
   29.00000      0.3236598    
   30.00000      0.3146394    
   31.00000      0.3004094    
   32.00000      0.3011326    
   33.00000      0.2845138    
   34.00000      0.2711502    
   35.00000      0.2601984    
   36.00000      0.2542473    
   37.00000      0.2385372    
   38.00000      0.2294970    
   39.00000      0.2189118    
   40.00000      0.2094501    
   41.00000      0.2009168    
   42.00000      0.1914005    
   43.00000      0.1806616    
   44.00000      0.1733572    
   45.00000      0.1603035    
   46.00000      0.1497179    
   47.00000      0.1414309    
   48.00000      0.1341241    
   49.00000      0.1241965    
   50.00000      0.1154761    
