# Course 1 Week 3 Quiz - row/column vector

There is one question is the quiz that I can’t really justify the answer for. I’d like to know what I’m missing.

The question involves picking options, one of which is: `w`(superscript)`[4]`(subscript)`3` is the row vector of parameters of the fourth layer and third neuron.

I selected this but apparently it’s wrong: it’s a column vector.

Why is this the case? We were taught that in the `W` matrix each row corresponds a neuron and each column to an input layer.

So wouldn’t it be the case that the third neuron would have a slice of parameters across the columns, i.e. it would be a row vector? (1 x n)

The weight matrix can have either orientation. There’s no universal agreement.

Hi TMosh. Sure, but in the context of this question in the quiz, it was assumed that the `W` matrix had rows representing each neuron of that layer.

Hello Hugo,

Refer this video again where Prof. Ng explains superscript square bracket number is column vector

A column vector is an nx1 matrix because it always has 1 column and some number of rows.
A row vector is a 1xn matrix, as it has 1 row and some number of columns.

one needs to understand input layer is column vector [4] and if that has number of examples that is represent with ( ) which can be row vector.

So the question where you are asking the superscript is [4 ] represent the input layer which is a column vector.

Regards
DP

Hi @Deepti_Prasad. Actually, it seems like the video after that one (“Computing a Neural Network’s Output”) mentions it in more detail. But thanks for linking that - I needed to pay more attention!

It isn’t really explained why this is the convention, but it seems like the rows of `W` are the transpose of the parameter vectors, which are column vectors. Thus in `W`, the row belonging to neuron 3 is a row vector, but it is actually the transpose of the original column vector `w`.

Would you say that this is correct?

Hello Hugo,

I think the confusion came from the below statement Prof. Ng mentions in the Computing a Neural Network’s output where he mentions

The first step and think of as the left half of this node, it computes z equals w transpose x plus b,

But one needs to understand the option w superscript[4], subscript(3) is explaining neuron which is a column vector where as W(l) is matrix with row equal to transpose of parameter vectors.

If you notice in the same question there is another option about W (one is capital W another small w, and both here different)

Regards
DP

Hi Deepti.

Yes that makes sense. So you are saying that `WX` is actually computed as `(W^T)X`, which explains why the individual rows of `W` in the latter case are actually column vectors?

Yup, actually if you see all the videos of this week, Prof.Ng explains it especially the video you mentioned in the previous comment.

Also I am going delete the previous image as it is part of grader quiz and that would be against community guidelines.

Regards
DP

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Thanks again. Clearly I need to make better notes!