Hi, In our data we have 10 people with 10 different attributes , we want to rank the people based on the weightage of these attributes. Suggest the best statistical method to do this. Does Revolution R solves my problem?? Regards, Lalitha Kristipati Associate Software Engineer ===========================================================================================================================Disclaimer: This message and the information contained herein is proprietary and confidential and subject to the Tech Mahindra policy statement, you may review the policy at http://www.techmahindra.com/Disclaimer.html externally http://tim.techmahindra.com/tim/disclaimer.html internally within TechMahindra. =========================================================================================================================== [[alternative HTML version deleted]]
Please don't cross-post to multiple lists. There is a Posting Guide
mentioned in the footer that you probably won't see because you are using
Nabble. It would have informed you that the R-devel mailing list was for people
interested in modifying R, definitely not this topic.
As to your question, Revolution R would probably be overkill, and if you chose
to go that route then asking the Revolution R support people for help would be
appropriate. This list is for the open source R software that RR builds on.
Your problem statement suggests you already know the weights... in which case
this is a straightforward linear algebra calculation that is trivial in R.
But your question mentions selecting statistics methods, which is not on topic
here in the R-help mailing list, since methods are independent of the software
used to apply them. If you know what methods you want to apply, and have read
the introductory R documentation, then this is an appropriate place to ask for
help on how to apply R to your problem. If that is the case, then DO read the
Posting Guide and try again with some example data and if possible some sample
results you expect to get. We can then show you how to connect the dots using R.
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Go...
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Sent from my phone. Please excuse my brevity.
On February 2, 2015 10:14:28 PM PST, Lalitha Kristipati <Lalitha.Kristipati
at techmahindra.com> wrote:>Hi,
>
>
>
>In our data we have 10 people with 10 different attributes , we want to
>rank the people based on the weightage of these attributes.
>
>Suggest the best statistical method to do this.
>
>Does Revolution R solves my problem??
>
>
>
>Regards,
>Lalitha Kristipati
>Associate Software Engineer
>
>
>
>===========================================================================================================================>Disclaimer:
This message and the information contained herein is
>proprietary and confidential and subject to the Tech Mahindra policy
>statement, you may review the policy at
>http://www.techmahindra.com/Disclaimer.html externally
>http://tim.techmahindra.com/tim/disclaimer.html internally within
>TechMahindra.
>===========================================================================================================================>
>
> [[alternative HTML version deleted]]
>
>______________________________________________
>R-help at 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.
Hi Lalitha, Your description is more like calculating a composite score from the values observed on ten attributes, which can then be ranked. Perhaps you want to standardize the observed values to insure that the result is not dominated by the attribute with the numerically highest variance. For example: V1<-rnorm(10,5,5) Z1<-scale(V1) You can then combine your ten standardized (Z) scores to form a composite score and rank your subjects on that. Jim On Tue, Feb 3, 2015 at 6:48 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote:> Please don't cross-post to multiple lists. There is a Posting Guide mentioned in the footer that you probably won't see because you are using Nabble. It would have informed you that the R-devel mailing list was for people interested in modifying R, definitely not this topic. > > As to your question, Revolution R would probably be overkill, and if you chose to go that route then asking the Revolution R support people for help would be appropriate. This list is for the open source R software that RR builds on. > > Your problem statement suggests you already know the weights... in which case this is a straightforward linear algebra calculation that is trivial in R. > > But your question mentions selecting statistics methods, which is not on topic here in the R-help mailing list, since methods are independent of the software used to apply them. If you know what methods you want to apply, and have read the introductory R documentation, then this is an appropriate place to ask for help on how to apply R to your problem. If that is the case, then DO read the Posting Guide and try again with some example data and if possible some sample results you expect to get. We can then show you how to connect the dots using R. > > --------------------------------------------------------------------------- > Jeff Newmiller The ..... ..... Go Live... > DCN:<jdnewmil at 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 February 2, 2015 10:14:28 PM PST, Lalitha Kristipati <Lalitha.Kristipati at techmahindra.com> wrote: >>Hi, >> >> >> >>In our data we have 10 people with 10 different attributes , we want to >>rank the people based on the weightage of these attributes. >> >>Suggest the best statistical method to do this. >> >>Does Revolution R solves my problem?? >> >> >> >>Regards, >>Lalitha Kristipati >>Associate Software Engineer >> >> >> >>===========================================================================================================================>>Disclaimer: This message and the information contained herein is >>proprietary and confidential and subject to the Tech Mahindra policy >>statement, you may review the policy at >>http://www.techmahindra.com/Disclaimer.html externally >>http://tim.techmahindra.com/tim/disclaimer.html internally within >>TechMahindra. >>===========================================================================================================================>> >> >> [[alternative HTML version deleted]] >> >>______________________________________________ >>R-help at 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 at 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.