In this video, we'll take a look at
another example of the independent
samples t-test in SPSS. And in this
example we have the variables treatment
and pain level. And we have two groups, as
we always do with the independent t,
for the variable treatment, where I
entered value labels and you can see
that the first group all receive the
treatment of acupuncture,
whereas the second group all received
the treatment of massage therapy.
And after receiving this treatment for a
period of two weeks, then they responded
on a 1 to 7 scale the amount of pain they
were currently experiencing at the end
of the last treatment, where 7 indicates
the highest degree of pain, and 1
indicates the lowest degree. So you can
see here that the first person, who
happened to receive acupuncture, had a
pain level of 6 at the conclusion of the
treatment. The second person had a pain
level of 5, and so on. The first person in
the massage therapy group had a pain
level of 6, the
second person had a pain level of 5, the third person
a pain level 7, and so on. So let's go ahead and
run the independent samples t-test. So we
select Analyze, Compare Means,
Independent-Samples T Test,
and then here pain level is going to go
in our Test Variable(s) box,
so we'll move that over there, and then
treatment is going to go into our
Grouping Variable, as this is the
variable that separates people into the
two groups.
Now we can see here that we use the
values of 1 and 2 to separate our
two groups. So go ahead and click on
Define Groups and enter a 1 for group 1 and
then a 2 for group 2. And then click Continue
and then OK.
Our output opens and we can see here
that there was a very small difference
between our two means, where the
acupuncture group reported a higher
joint pain than did the massage therapy
group, but that difference is pretty
small.
Moving to our Independent Samples T Test
table, here we're going to interpret
whether or not the test is statistically
significant.
First recall that we interpret the
results of our Levene's test. And, as a
reminder, the decision rule is as follows:
if p is less than or equal to
.05, the variances are significantly
different and we want to interpret the
bottom row of results for t,
whereas if p is greater than
.05, the variances are not significantly
different and we want to interpret the
top row of results for t. Looking at
these two conditions here,
which does ours fall into? We have a p of
.873, and that falls into the second
condition here, so therefore the
variances are not significantly
different, and we'll go ahead and interpret the
top row of results for t. So we're going to
look at these values here in the top row
for t.
And recall the decision rule for
assessing of the t is significant,
using alpha .05, is we look at this
p-value, and if p is less than or equal
to .05, the test is significant,
which indicates the pain levels differ
significantly for the acupuncture and
massage therapy groups. Whereas if p is
greater than .05, the test is
not significant, indicating that the pain
levels do not differ significantly for
the two groups. So we see a p of .494 and
you should see that, of these two
conditions, .494 is in fact greater than
.05, therefore the test is not
significant, meaning that the pain levels
do not differ significantly for the
acupuncture and massage therapy groups.
Next we'll write these results using APA
format. We could write these results as
follows:
There was not a significant difference
in the reported pain levels for those
who received acupuncture and massage
therapy as treatment. Then here we have
t, once again indicating that we have
an independent samples t test, 28 degrees
of freedom, which is equal to the total
sample size of 30-2,
We have a t of .69,
which is given here rounded to two decimal
places, and finally our p-value of
.494, which is shown here.
Now you can state p is greater than
.05, instead of stating the
exact p-value if you prefer.
However, as always, stating the exact
p-value is more informative.
So, once again in summary, our test here
showed that there was not a significant
difference in the joint pain between the
acupuncture and massage therapy groups.
This concludes the presentation on the
independent samples t test in SPSS.
Thanks for watching.