Howdy

I apologize for duplicated posting. But I decided to correct my previous
posting.

I had the regression results using

r <-  lm(Y ~ nemp + as.factor(devt), data=d).

First, there is the result of anova(r). Here I could not find regression
coefficients.

Response: Y
                       Df Sum Sq Mean Sq F value  Pr(>F)
nemp                    1   58.2    58.2 1233.23 < 2e-16 ***
as.factor(devt)        3    3.6     1.2   25.69 2.6e-16 ***

Second, there is the result of summary(r) that I am confused
with too many coefficients for a factor variable "devt".
Because there are three coefficients for factor variables
such as"as.factor(devt)A ", "as.factor(devt)B", "as.factor(devt)C".

Coefficients:
                                  Estimate Std. Error t value Pr(>|t|)
(Intercept)                       as.factor(devt1)        3    3.6     1.2
25.69 2.6e-16 ***   5.95e-02   10.19  < 2e-16 ***
nemp                              2.87e-06   1.04e-07   27.63  < 2e-16 ***
as.factor(devt)A            2.44e-02   1.47e-02    1.66  0.09630 .
as.factor(devt)B           -1.10e-01   1.40e-02   -7.90  4.6e-15 ***
as.factor(devt)C          -9.19e-03   1.53e-02   -0.60  0.54953

Is this model right  as a tentative model at least?
   Y = 6.07e-01  + 2.87e-06* nemp + 2.44e-02 * as.factor(devt)A
         - 1.10e-01 * as.factor(devt1)B - 9.19e-03 * as.factor(devt)C


 And so, my question is "which coefficients should I use for a final
model?".

Thanks in advance,
-- 
Kum-Hoe Hwang, Ph.D.Phone : 82-31-250-3516Email : phdhwang@gmail.com

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