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 â***â 0.001 â**â 0.01 â*â 0.05 â.â 0.1 â â 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 <[EMAIL PROTECTED]> 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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]]
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.