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Multiple Regression in Excel - P-Value; R-Square; Beta Weight; ANOVA table (Part 1 of 3) - YouTube
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In this video we'll take a look at how
to run a multiple regression analysis in
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Microsoft Excel. Now in this example,
notice that we have four variables:
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college GPA, and that's the GPA after the
first year in college, and then we have
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SAT score, which was taken in high school,
and we have social support, and this was
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a measure of how supported people feel,
to what degree they can turn to
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others for support, and this was also
assessed in college, and then we have
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gender, where we have 1s and 2s, where 1s
are males and 2s are females. So in this
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example, we have a total of four
variables and we have 30 rows of data
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here. And in regression, each row
corresponds, most typically, to a
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different person. So, for example, the
first person had a GPA of 3.45 after their
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first year in college, they had a 1200 on
the SAT, a 62 on social support, and
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they were male, they had a 1 on gender. Now
in multiple regression, we have two
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different kinds of variables, we have the
criterion variable, which is also known
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as the dependent variable, and in this
example the criterion variable is
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college GPA. And then we have predictor
variables, and those are also known as
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independent variables. Here we
have 3: SAT score, social support, and
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gender. And, in multiple regression, we are
always going to have at least two
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predictor variables, or independent
variables, and only one criterion
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variable, or dependent variable.
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So it's important to get used to this
terminology when you're using multiple
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regression as it can get a little
confusing otherwise. So, once again,
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college GPA is our criterion variable, or
our dependent variable, and these three
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variables are our predictors, or our
independent variables. And what we're
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trying to do in multiple regression is
we're trying to use these predictors, SAT
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score, social support, and gender, to
predict our criterion variable, college
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GPA. And that's at the end of the first
year in college once again. And there's
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one other thing I do want to note here,
I have a dichotomous variable here, gender.
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Of course for gender, there's two values males
and females. And that's fine, if I have a
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dichotomous variable, I can go ahead and enter
that into regression as normal. But if I
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have a categorical variable that has
more than two categories, like say
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ethnicity, let's say we had four
categories in ethnicity,
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I can't just go ahead and enter that as
a normal predictor, but instead I have to
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recode that where I have to have as many
predictors for ethnicity as are equal to
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the number categories minus one. So if I
have, for example, four categories of
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ethnicity, I would need to create three
predictors for ethnicity alone so they
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would be ethnicity 1, ethnicity 2,
ethnicity 3, just for that variable.
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And how to do that is beyond the scope
of this video, but it is important to be
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aware of.
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So if you do have a categorical variable
that has more than two categories you
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don't want to just go ahead and enter it
into the normal multiple regression
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commands as we're going to do here in
Excel. It needs to be re-expressed. But
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we're good to go with gender, because
there's just two categories, or in other
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words it's dichotomous.
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OK so let's go ahead and get started. To run
the multiple regression in Microsoft Excel,
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we want to go to Data and then select
Data Analysis. And then the Data Analysis
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window opens. We want to go ahead and
scroll down to find Regression. Select
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that and then click OK. Now here for
Input Y range, Y corresponds to our
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criterion variable, and X corresponds to
our predictors. So let's go ahead and
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start with our Y, since the cursor's flashing
in that box. Go ahead and select college
GPA and
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scroll all the way down to select all
the values. Then we see B1 through B31
in that box.
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That looks good.
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Go ahead and make sure now that you
click on the Input X range box, so that
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it's active. And then now we'll select
our three variables and all the values
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for SAT score, social support, and gender.
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OK that looks good. So now I have C1
through E31, that's perfect.
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Next, notice that I did select my labels
which I wanted to do. I have the variable
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names there. So I'm going to go ahead and
click on Labels. OK and everything else
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looks good, so go ahead and click OK. And
then here we get our output and it's a
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little bit compressed so let's go ahead
and modify this. First, let's go and
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change the font to 13 point. And then I'm going
to go ahead and expand this by double-
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clicking on these columns here; that
looks good.
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