How to do correlation from data with series

Hi i have to make corelation to check the dependance of variable c from series 1 or 2. Can I split t vector into two one t1 and t2 make 2 seperet correlations of t1 to c1 and t2 to c2?

t=[21,22 ,323,43,231,53,23,12,53,12]
c=[23,12 ,223,333,21,63,24,23,763,14]
p={"1","1","1","1","1","2","2","2","2","2"}

[Adam Danz]

Note that if you're using string arrays, use square brackets.

p=["1","1","1","1","1","2","2","2","2","2"];

Answer 1

[Adam Danz]

You can use xcorr and indexing.

t=[21,22 ,323,43,231,53,23,12,53,12];
c=[23,12 ,223,333,21,63,24,23,763,14];
p=["1","1","1","1","1","2","2","2","2","2"];  % <-- String array with square brackets

[groupID, groups] = findgroups(p)

groupID = 1×10

1 1 1 1 1 2 2 2 2 2

groups = 1×2 string array
    "1"    "2"

xcorr(c(groupID==1), t(groupID==1))

ans = 1×9

0.0531 0.0376 0.5946 0.9089 0.9195 1.1362 0.1879 0.0745 0.0044

xcorr(c(groupID==2), t(groupID==2))

ans = 1×9

0.0756 0.3627 0.2304 1.2112 4.4774 1.1699 1.8936 4.0761 0.0742

or use splitapply

splitapply(@(x1,x2){xcorr(x1,x2)}, c, t, groupID)

ans = 1x2 cell array
    {1×9 double}    {1×9 double}