On Thu, Nov 8, 2012 at 6:59 AM, Deba Ranjan <[email protected]> wrote: > Dear Experts, > > Thanks for the Quick response, Yes i have gone through that > "help.start()", but i did not understand what exactly it is. i hope might be > i am very new to this field or might i did not understand well in going > through. But all i know is very quite eager to learn this. i have set of > data file which i need to analysis such as- > Factor Analysis, Cluster Analysis, Discriminant Analysis, Correlation and > regression, Analysis Of variance, Descriptive Statistics and hypothesis > testing. > > Can you please explain me how to analysis the provided above criteria. > Please help me in this study. i will thankful to you advice and suggestion. > > i have provided an attachment (Same in both the Format .CSV and .R), which > i need to study the criteria. Please help in by step by step how to do that. > > Please explain me how to read the data , if i open the both the file i > finds that both the two file seems to be quite different. Please help me out > of this. > > > Regards, > Debaranjan >
Hi Deba, This unfortunately seems like you're just looking to apply a list of statistical buzzwords that you've found with no real rational for any of them in particular. This isn't a statistics tutoring service, so your request falls outside the remit of this list. If you have statistical methods you wish to implement, but aren't sure how to do them in R, that's a different matter. If you've worked though the Introduction manual with no troubles, I'd suggest you get a proper statistics text to supplement your understanding: Modern Applied Statistics with S by Venables and Ripley is a particular favorite. However, you might wish to find a more introductory text before taking on MASS. Cheers, Michael ______________________________________________ [email protected] 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.
