no music versus low volume. Take a moment
to follow along with me here, to make
sure you can line these up in the table.
No music versus low volume had a p of
.963, so that's none versus low, p =
.963. And then no music vs high-volume,
none vs high, had a p of .027, 8 00:00:24,420 --> 00:00:29,970 you can see that right here. And then low
volume versus high volume, this result
right here, low versus high, had a p of
.049, and you can see that right
here. And we found that this first test
was not significant and the latter two
tests were significant. So no music vs
high, low volume versus high volume.
So if we look at these means here, I have
the means presented here, and they were
obtained by going to the Descriptives
table. So notice these here 84.90, 84.20, and
77.50. These are just displayed once again
here, you see the three matched up. OK so
I have the means here to make this a
little bit easier, and for the
significant results, what I want to do is
see which group had the better exam
performance. So for no music vs high-volume,
notice the no music mean is 84.90, while the
high-volume mean is 77.50.
Since it was significant,
this indicates that no music performed
significantly better than high
volume, so I'm going to write this here.
No was greater than high, just
short-handed there.
And then low volume versus high-volume
was also significant, this was very close,
but it was in fact significant. So let's
compare these two means. Low is 84.20 and
high is 77.50, so we can see here that the
low volume group performed significantly
better than the high volume group, so
we'll write that here. Low greater than high,
just short-handing in our results. And then,
once again, no music versus low volume
was not significant.
So we could summarize the results at this
point - these are all our tests - there was
not a significant difference between no
music and low volume
and then we could say that the no music
condition and the low volume condition,
these were both significantly higher
than the high volume condition.
Now let's take a moment to look at our
final table, the Homogeneous Subsets
table.
And the way to interpret this table is
as follows: groups that share the same
column are not significantly different,
so if groups share column, there's no
difference. Groups that do not share
the same column, are significantly
different.
So let's take a look at that in our
table here. Let's start with the groups
that share a column. Notice here in column
2 we have low volume and we have none or
no music, no volume, these two groups
share column 2. So that means that,
since they share the same column, they
are not significantly different.
So we would say low and no volume are
not significantly different.
However, once again, groups that do not
share the same column are significantly
different.
So notice that the high volume group is
in its own column; it doesn't share the
same column with low and none which is
right here. So this indicates, since they
don't share the same column, this
indicates that low volume and none are
in fact significantly different than
high. And the nice thing about this table
is not only is it not redundant as was
the Multiple Comparisons table, where
it presented every result twice, but it also
has the means inside the table, so I know
that low and none are significantly
different than high. But I can actually
see the means here as well, so when I
know there's a difference, all I have to
do is look at the means and see which
ones are higher. So I can see that low
volume and none are in fact higher than
high volume, so they're significantly
higher in terms of exam scores than the
high volume group.
So I could summarize these results as
follows: there was not a significant
difference between the low volume and
the no volume group, you see that right
here,
however the low volume group and the no
volume group were significantly higher
than the high volume group. So, once again,
these two tables will give you the same
results, they're just presented somewhat
differently. Now some post-hoc tests are
presented with this type of table, and
then some are presented with this type
of table as well. But some of the tests
available under the Post Hoc button do
not have this type of presentation at
all.
We're going to focus on Tukey's test,
because research indicates that it's a
pretty good test, and it still does a
good job at keeping our alpha at .05
overall. this concludes the discussion of
post-hoc tests for the one-way ANOVA.
Thanks for watching.