- [Charlie] In this short screencast,
I'm gonna show you how we can analyze
a factorial design in Minitab.
The example I'm going to be going over is the same example
that we worked through in a previous Screencast
on higher order factorial designs.
We've got our coded variables here
and we have our responses.
Now, n equals two, this is a replicated experiment,
so we have to keep that in mind.
So let's go over to Minitab.
The first thing we wanna do is go to Stat, DOE, Factorial
and we have to create a factorial design.
This is the best way to do this.
There's a couple options here.
We have three factors,
so we have to change this to three factors.
We can look at the designs
because we wanna specify a full factorial design.
Next week you're gonna learn about a 1/2 fraction,
fractional factorial designs,
but we wanna select a full factorial design.
We don't have any center points,
but we do have two replicates.
We have two replicates of each
of what we call corner points.
We can select OK.
Click in options
and make sure that you deselect randomized runs.
If you have not yet collected the experimental data,
you wanna randomize runs
because this will kind of tell you the order to put them in.
And that's kind of typical
if you have not already collected the data.
We already have the data, so deselect randomized runs,
and that will put it in sort of a standard order.
And then we can select OK.
It comes out with this.
We have our standard order.
I never know why it gives us center point and blocks
'cause we don't even use that,
but A, B, and C, those are our three different factors.
And it tells us kind of the standard order there
and the various levels.
Now that we have that created,
we can go back over here to Excel,
and I'm gonna just copy this.
Go back over to Minitab and I'm gonna paste here.
But you notice that since we selected two replicates,
it actually has stacked them on top of one another.
So let's bring this up.
In other words, it has put one of the replicates here
and then it's just repeated itself down here.
So this second half is repeated.
Our second replicates, I can do control cut,
control paste, control V,
and let's just name this Y for our responses.
Now that we've created this factorial design,
we can go up here to Stat, DOE, Factorial,
Analyze Factorial Design, click on that.
The response is C8, which is our our Y value.
And there's some different things that you can do here.
We're just analyzing to do a quick screening
to see which ones are significant.
You can mouse around here
if you wanted to change the different terms,
but by default it's gonna add all of those terms.
If you wanted to look at the residuals
of the model that's created, you could do that here,
but we're just gonna go ahead and click OK.
And it goes through
and it spits out both of the statistical approaches
that we've been doing.
This top one is the T distribution-based analysis.
It's calculating the P-values, the test statistics,
and so if you compared this to what we did in Excel,
you would see that it's exactly the same.
And also it goes through
and does the analysis of variance approach.
It looks a little different
because it's itemizing by linear models,
two way interactions, and three way interactions,
but in the end, it's exactly the same.
It also spits out this regression equation in uncoded units.
That's not entirely true
because we put our data in terms of coded units.
So this is actually in terms of coded units,
so keep that in mind because our data is in coded units.
So that's how we can use Minitab
to analyze a factorial design.