Given Matrix

S1=[1 1 0 0 1]

S2=[1 0 0 0 0]

S3=[1 1 1 1 0]

S4=[0 0 0 1 0]

S5=[0 1 1 1 1]

Output will be the correlation of :

{S1,S2}=

{S1,S3}=

{S1,S4}=

{S1,S5}=

{S2,S3}=

{S2,S4}=

{S2.S5}=

{S3,S4}=

{S3,S5}=

{S4,S5}=

Given Matrix

S1=[1 1 0 0 1]

S2=[1 0 0 0 0]

S3=[1 1 1 1 0]

S4=[0 0 0 1 0]

S5=[0 1 1 1 1]

Output will be the correlation of :

{S1,S2}=

{S1,S3}=

{S1,S4}=

{S1,S5}=

{S2,S3}=

{S2,S4}=

{S2.S5}=

{S3,S4}=

{S3,S5}=

{S4,S5}=

Try to take a look at `cor()`

, e.g.:

```
X = matrix(data = rnorm(100), nrow = 10, ncol = 10)
cor(x = X, method = "pearson")
```

It depends on what kind of correlation you want to calculate. See the below guide for getting started with calculating correlation in R.

https://www.statmethods.net/stats/correlations.html

In the spirit of the forum, it's best to give it a go yourself, and then, if you get stuck, include a reprex (short for minimal **repr**oducible **ex**ample) with your code, and we can help you troubleshoot from there!

I have 409 by 610 binary matrix. I want to fin out the correlation like above demonstration using pearson method.

R studio programming, using "for loop" find out the correlation (method = "pearson") of Given value :

F1 F2 F3

1 0 1

0 1 0

0 1 0

1 1 1

0 1 1

Output will be

R12 = cor (F1, F2) = ?

R13= cor (F1, F3) = ?

R23= cor (F2, F3) = ?

and save the output in excel file

Hi Farhad, be sure if you can, to ask your programming question as a reproducible example.

The **correlation between two vectors** in R is the `cor`

function. For example;

```
x = 1:3
y = 4:2
cor(x,y, method = "pearson")
#> [1] -1
```

Created on 2018-05-11 by the reprex package (v0.2.0).

It looks like you're dealing with a data frame. And it looks like you want to get all the combinations of columns?

```
df = matrix(c(2,4,3,1,5,7,1,2,3,5,8,2,4,5,1,1,3,6,1,3,4,5,6,1),nrow=6,ncol=4,byrow = TRUE)
df = as.data.frame(df)
df
#> V1 V2 V3 V4
#> 1 2 4 3 1
#> 2 5 7 1 2
#> 3 3 5 8 2
#> 4 4 5 1 1
#> 5 3 6 1 3
#> 6 4 5 6 1
cor(df, method = "pearson")
#> V1 V2 V3 V4
#> V1 1.0000000 0.7385489 -0.2533202 0.0000000
#> V2 0.7385489 1.0000000 -0.4287465 0.6324555
#> V3 -0.2533202 -0.4287465 1.0000000 -0.1898142
#> V4 0.0000000 0.6324555 -0.1898142 1.0000000
```

Created on 2018-05-11 by the reprex package (v0.2.0).

You'll want to extract all those combinations in the last table.

How comfortable with R are you at this point?