Hi Christian,
please give always reproducible code,
so we can see what have done
and  give you the best answer.

lm function, generally 
as in this  example form lm man page ( ?lm)

 
> trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
>ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
>reg=lm(trt~ctl)
>summary(reg)

Call:
lm(formula = trt ~ ctl)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.09389 -0.33069 -0.15249  0.05128  1.45497 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)   
(Intercept)   7.7957     2.1661   3.599  0.00699 **
ctl          -0.6230     0.4279  -1.456  0.18351   
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 0.7485 on 8 degrees of freedom
Multiple R-squared: 0.2095,    Adjusted R-squared: 0.1106 
F-statistic:  2.12 on 1 and 8 DF,  p-value: 0.1835 


Returns you all the  answer (almost) for the  questions that you ask;
the p-value of the intercept line, is the p-value from the 
test( t test)  if the intercept is  different form zero. 
the ctl line has also the same interpretation, regarding the value returned.
Meaning no is not significantly different form zero.

If you want to test if the  estimates ( slopes or intercept) are
different from a specific value as in your case different for 0.5
you can apply a test. 
Type on R 
?t.test 
and you can find the  all the information you need.

Hope this helps

Best Regards

Anna

Anna Freni Sterrantino
Ph.D Student 
Department of Statistics
University of Bologna, Italy
via Belle Arti 41, 40124 BO.




________________________________
Da: Christian Arnold <chrarnold@web.de>
A: r-help@r-project.org
Inviato: Martedì 9 dicembre 2008, 21:54:23
Oggetto: [R] Significance of slopes

Hello R community,

I have a question regarding correlation and regression analysis. I have two variables, x and y. Both have a standard deviation of 1; thus, correlation and slope from the linear regression (which also must have an intercept of zero) are equal.
I want to probe two particular questions:
1) Is the slope significantly different from zero? This should be easy with the lm function, as the p-value should reflect exactly that question. If I am wrong, lease correct me.
2) Is the slope significantly different from a non-zero value (e.g. 0.5)? How can I probe that hypothesis? Any ideas?

I apologize if this question is too trivial and already answered somewhere, but I did not find it.

[[elided Yahoo spam]]
Christian

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