## Help with PCA analysis

### Elise (view profile)

on 19 Sep 2013

I have a set of measurements of wrist movements. It contains data about the movements in x,y,z translations and x,y,z rotations - so it has 6 dimensions.

I used:

```[coeff,score,~,~,explained,~] = pca(E);
```

Explained gives me the following result:

```[56,0982092469235;
26,0254466244066;
11,3132049655197;
5,01572264188474;
0,929970860888532;
0,617445660376905]
```

From this I see that 80% of the data is in the first two principle components.

I assume that these 2 principle components form a plane. How do I use coeff to see how this plane is orientated?

Thanks in advance for helping me out!

the cyclist

### the cyclist (view profile)

on 19 Sep 2013

When you say "see how this plane is orientated", do you literally mean a visualization? It's a challenge to show a (2-D) plane embedded in a 6-D space.

Elise

### Elise (view profile)

on 20 Sep 2013

Good question, visualizing would be preferable, but I can see that that would be difficult.

I quess what I want to know is how much of each original component can be found in the first two principal components. For this case: how much translation v.s. rotation can be found in the first to principle components.

I know this should be found in coeff/score, I just can not figure out how to interpret these.

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