[R] Data transformation for chi-square test.

[Charlie Chi]

Dear all R users
:
I am a IT student with few statistical background and new R user for only 
have  two month exprience. I have a data named medcost, import by 
read.table() as follow for example (real dataset has 500 cases), the 
heander id means case id, member means members in a family and cost is the 
family pay for medical cost every 6 months.

id        member               cost
1         4                          320
2         2                          150
3         3                          420
4         5                          330
5         6                          540
6         2                          310
7         4                          169
8         6                          647
9         3                          347
10       4                          567

I would like to use this dataset with chi-sqare analysis to see if there is 
any realationship between family member and medical cost (more members in a 
family will rise their medical cost?) I have found the pacage called stats, 
but I think need to transform the dataset into a contingency table as I 
read from books. I am not sure if I correct, I think the table should looks 
like:
                      member
cost                [2]      [3]     [4]     [5]     [6]     Total
[0,100]           1         0        0        0       0          1
[100,200]       0         0        1        0       0          1
[200,300]       0         0        0        0       0          0
[300,400]       1         1        1        1       0          4
[400,500]       0         1        0        0       0          1
[500,600]       0         0        1        0       1          2
[600,700]       0         0        0        0       1          1
Total              2          2       3         1       2         10

I did try to use the method in chapter 5.0 of "R Introduction" to create 
freqency table, but it did not work. I am wondering if any one can help me 
with it? Thank you for your help.

Regards

Charlie
.