Dear Lalitha, see inline below
On 03/05/2015 10:19, Lalitha Viswanathan wrote:
> Hi
> I have a dataset of the type attached.
> Here's my code thus far.
> dataset <-data.frame(read.delim("data", sep="\t", header=TRUE));
> newData<-subset(dataset, select = c(Price, Reliability, Mileage, Weight,
> Disp, HP));
In fact in the file the variable seems to be called Disp.
> cor(newData, method="pearson");
> Results are
> Price Reliability Mileage Weight Disp
> HP
> Price 1.0000000 NA -0.6537541 0.7017999 0.4856769
> 0.6536433
> Reliability NA 1 NA NA NA
> NA
> Mileage -0.6537541 NA 1.0000000 -0.8478541 -0.6931928
> -0.6667146
> Weight 0.7017999 NA -0.8478541 1.0000000 0.8032804
> 0.7629322
> Disp 0.4856769 NA -0.6931928 0.8032804 1.0000000
> 0.8181881
> HP 0.6536433 NA -0.6667146 0.7629322 0.8181881
> 1.0000000
>
> It appears that Wt and Price, Wt and Disp, Wt and HP, Disp and HP, HP and
> Price are strongly correlated.
> To find the statistical significance,
> I am trying sample.correln<-cor.test(newData$Disp, newData$HP,
> method="kendall", exact=NULL)
> Kendall's rank correlation tau
>
> data: newx$Disp and newx$HP
> z = 7.2192, p-value = 5.229e-13
> alternative hypothesis: true tau is not equal to 0
> sample estimates:
> tau
> 0.6563871
>
> If I try the same with
> sample.correln<-cor.test(newData$Disp, newData$HP, method="pearson",
> exact=NULL)
When I try that it works fine.
The real question is why when you asked it for the Pearson coefficient
it decided to give you the Spearman as the warning message below points
out. I suspect you have done something else which you did not tell us about.
> I get Warning message:
> In cor.test.default(newx$Disp, newx$HP, method = "spearman", exact = NULL) :
> Cannot compute exact p-value with ties
>> sample.correln
>
> Spearman's rank correlation rho
>
> data: newx$Disp and newx$HP
> S = 5716.8, p-value < 2.2e-16
> alternative hypothesis: true rho is not equal to 0
> sample estimates:
> rho
> 0.8411566
>
> I am not sure how to interpret these values.
> Basically, I am trying to figure out which combination of factors
> influences efficiency.
>
> Thanks
> Lalitha
>
>
>
> ______________________________________________
> 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.
>
--
Michael
http://www.dewey.myzen.co.uk/home.html