Technically it is not on topic to discuss the statistics behind R calculations here, and certainly not our job to do so within the context of your educational institution's schedule. However, you have the power to read the source code of any function in R or contributed packages, so go for it. Just enter the name of most functions without parentheses at the R command line. Page 43 of [1] should help for more deeply hidden code.
[1] http://cran.r-project.org/doc/Rnews/Rnews_2006-4.pdf --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<jdnew...@dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --------------------------------------------------------------------------- Sent from my phone. Please excuse my brevity. On May 19, 2015 1:37:13 PM PDT, Livia Maria Vestergaard <lves...@student.sdu.dk> wrote: >Hi :) > >I have an an examination tomorrow, and don't quite understand how R >calculated the values. > >Yes. You are right R^2=0.02166 :) >As mentioned It is a dummy variable model with the 5 regions of >Denmark as 4 independent dummy variables and price as the dependent >variable. > >price = 10.325 - 0.176*Sjaeland - 0.368 * NJylland - 0.230*MJylland - >0.120* Syddanmark > >I will probably be asked how to interpret the standard error = 0.7348 >on 342199 degrees of freedom (= 342 204 observations - 5 categories); >about the 5 standard errors for the beta values, the F-statistic = 1894 >on 4 categories and the p-value ≈ 0. But I don't quite understand how R >reached the outputs and what parameter are F-distributed, what the >standard errors says something about and the standard errors and the >F-statistic = 1894 when it is a dummy variable model. > >Hopefully the answer is out there somewhere and you can help :) > >Best Livia >________________________________________ >Fra: Livia Maria Vestergaard >Sendt: 19. maj 2015 10:16 >Til: r-help@r-project.org >Emne: [R] Output interpretation: standard error of lm dummy variable > >Hi guys > >I have a statistical question to an analyse I ran in R. It is a dummy >variable model with the 5 regions of Denmark as 4 independent dummy >variables and price as the dependent variable: > >price = 10.325 - 0.176*Sjaeland - 0.368 * NJylland - 0.230*MJylland - >0.120* Syddanmark > >I understand the R^2 = 0.7348 - that it shows the explanatory force of >the model (between 0 and 1) >My question is simply how to interpret the standard error = 0.7348 on >342199 degrees of freedom? How is it calculated when the model is a >dummy variable model. And what does it mean that the F-statistic says >that there are 1894 on 4 and 342199 DF (degrees if freedom?) with a >p-value < 0? > >I have been searching for hours - and can't quite figure out how R >reached the numbers and how to interpret the output of standard error >and the p-value of the dummy model. > >I really hope you can help :) > >Best Livia > > >------------------------------------------------------------------------ > >______________________________________________ >R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >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. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
