Does applied/computational linear algebra satisfy admissions requirements?

[Geococcyx]

(I have to assume this has been answered, but I guess I didn't find the right search terms.  Oh well...)

As the title asks, do applied or computationally-based linear algebra classes satisfy the basic requirements for admissions to grad schools in statistics or biostatistics?  I'm going to assume that it's probably on something of a school by school basis, so if any of y'all who have recently applied in similar circumstances would like to chime in regarding places you did/didn't get considered, that may be helpful.

I seem to recall cyberwulf or someone of similar stature saying that everyone should take proofs-based linear algebra, and while I'm intending on it, if applied linear algebra just straight-up is never accepted then clearly I need to schedule the proofs-based version this upcoming semester as opposed to in the spring.

Panic-posting about admissions requirements after midnight is super fun, so I hope (as opposed to my last post) that this might actually help a few other worried folks.

[bayessays]

You're fine, don't worry about it.  Most intro linear algebra classes are mostly applied with some proofs thrown in.  It's pretty rare for people to take a really proof-based first linear algebra course.

[cyberwulf]

Outside of the most intensely mathematical stat programs, the linear algebra requirement is there to ensure that you know what vectors and matrices are and how to do basic operations with them. For example, you should be able to interpret what (X'X)^(-1)X'y means (with X a matrix and y a vector). It's nice but not essential to have seen eigenvalues, eigenvectors, and various matrix decomposition techniques.

[dmacfour]

I took a linear algebra class that said it was computational, but you couldn't tell that from the transcript and there were proofs on just about every page of the textbook. You could do what I did and study the proofs, even if they aren't required.