Question: I am trying to find the right statistical procedure to use to analyze a set of course enrollment data for students. The enrollment data is binary (0/1) for a large number of a group of students. I would like to understand which courses are commonly chosen together by students. For example, a segment of data may look like this:

```
student Id    precalc    algebra    statistics   calculusBC   englishlit  (etc)
100104        0          1          1             0           0
100105        1          1          0             0           1
100106        1          0          0             1           1
100107        0          0          1             0           0 
100108        0          0          1             1           1
(etc.)

```

What's the right procedure to analyze data of this type to suggest that certain courses are commonly elected in pairs or groups with other courses?

Answer: 
Clustering does not work very well on binary data.

Consider using Apriori instead to find **frequent combinations**.

But don't expect too much from the data. You only have a few bit of effective information there. That is barely enough to talk about "duplicate records".
1.we can also use k-mean process to categorize the students result.
2.we can classify students according to the same and common subject selection and keep them into the same group.