On May 11, 2013, at 06:10 , meng wrote:
> Hi all:
>
> I have a question about one-way anova.
>
> The data is ??sleep??which belongs to R.
>
>
>
> code1:
>
> summary(lm(extra~group))
>
>
>
> Estimate of group2(1.58) is the difference between mean of group1 and
group2,and t value(1.861) and p value(0.0792) is the same as 2 sample t test,and
the code is ?? t.test(extra~group)??.
>
>
>
> My question:
>
> The p value of Intercept(0.2276) tests for what?
>
>
>
> My guess is test the difference between mean of group1 vs 0:
>
> dat1<-extra[group==1]
>
> t.test(dat1,mu=0)
>
>
>
> But the p value is 0.2176,which is different from 0.2276 of lm result.
>
>
>
>
>
>
>
> code2:
>
> summary(lm(extra~group+0))
>
>
>
> The pvalue of group1(0.2276) and group2(0.0011).
>
>
>
> My question:
>
> The p value of group1 and group2 tests for what?
>
>
>
> My guess is test the difference between mean of group1 vs 0 and group2 vs
0:
>
>
>
> dat1<-extra[group==1]
>
> t.test(dat1,mu=0)
>
>
>
> The p value is 0.2176,which is different from 0.2276 of lm result.
>
>
>
> dat2<-extra[group==2]
>
> t.test(dat2,mu=0)
>
>
>
> The p value is 0.005076, which is different from 0.0011 of lm result.
>
>
>
>
>
> So,what??s wrong with my guess?
>
You need to pay more attention to the degrees of freedom for error.
--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com