[R] help neede fast

[gauravbhatti]

Hi all can any one of you write a script for the following problem

Let X be a matrix of random normal values (mean =0; sd=1) (see rnorm()
function) having 10 columns and N=100 rows. Let the first row in the matrix
be (1,1.5,1.4,3,1.9,4,4.9,2.6,3.2,2.4). Assume that the first 5 columns of
data for each row correspond to a group A, while the remaining 5 to another
group B.

For each row of the matrix X, compute:
a) the t-statistic comparing the groups A and B assuming equal variance 
b) Compute the probability to observe such a t-statistics only by chance,
using a permutation analysis. The following strategy will be used: the
columns will be randomly permuted nk=100 times, and at each iteration the
t-statistic will be computed again and recorded in a vector. At the end,
compute the p-value as the number of times out of nk when the t-statistic
with the permuted data was at least as or more extreme than the t-statistics
obtained with the real (non-permuted data).   
Present the result as a dataframe with 3 columns: ID= Row number, t=
t-score, p=p-value; 

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