We've already seen one way to create a bar chart using the frequencies command.
We plotted the independent measure of gender, and we learned how to add error
bars to repeated measures bar charts, so now we're going to plot a bar chart with
error bars for independent measures, using the chart builder. Then we can
compare the error bars to see whether they overlap. When error bars overlap
that suggests the groups are actually pretty similar, even if one bar is higher
than the other. But when the error bars do not overlap, that suggests that the
group means are probably different. We're still using "clickers.sav" be sure to use
your new corrected data set that we fixed in the last video. This time our
research question is whether students who share a single clicker within a
group prefer to have an individual clicker more than students who have
individual clickers, and is there a gender difference in preference for an
individual clicker. The independent variable was group assignment, "shared
clicker" group versus "individual clicker" group that goes on the x-axis. The
dependent variable or outcome measure is the mean preference for an individual
clicker. That will be plotted on the y-axis. Preference was measured using a
Likert type rating scale with scores ranging from 1 to 7, with 7 indicating a
high preference for an individual clicker, and 1, low preference for an
individual clicker. Create a bar graph to determine whether students prefer to
have their own individual clicker. So we'll go to graphs and chart builder. We'll
click reset, and remember that when you're seeing variable labels you can
right-click or control-click to display variable names
or to display the variable labels. Let's choose variable names. And now we're
going to go to the bar option and drag the simple bar chart up into the canvas.
This time we're going to drag the variable "prefer" to the y-axis, and we're
going to split it by group. That will go on the x-axis. In the element properties
window, let's make sure that "mean" is selected under "statistic". We'll display
error bars and leave the confidence interval set to 95%. The bar style is set
to bars who are ready to go, click apply and ok, let's look at the resulting bar
chart. We see that preference for an individual clicker was lower in the
shared clicker group than it was in the individual clicker group. To interpret
these findings I want you to notice how the bottom of the taller error bar does
not overlap with the top of the lower error bar the non-overlap of the error
bars is a good hint that these two groups are likely statistically
significantly different. We should do a t-test to find out, but just from the
graph we can get a good idea. So how would you interpret these findings? We
assumed that everyone would prefer having a clicker all to themselves. Using
the preference of the individual clicker group as a baseline, we were surprised to
see that preference for an individual clicker was lower in the group that had
the experience of sharing a clicker with the group. One interpretation of these
findings is that students who actually get to experience sharing a clicker with
a group discover that sharing a clicker does not detract from the experience
perhaps people think they prefer having an individual clicker because that's how
clickers are typically used. Once they have the shared clicker experience, they
realized that having an individual clicker does not really add that much.
Certainly the shared clicker group was not clamoring for their own individual
clicker after the experiment. So reflecting on these
findings, we begin to wonder if perhaps males want their own clicker more than
females. Are females more into sharing? Is there a gender difference in preference
within each group? We could answer this within ANOVA, but we can accomplish it
easily with graphing. I would like to examine these same findings splitting
them by gender. So how do we divide a bar chart by group and gender? We're going to
go to graphs > chart builder. This is the example that we've just run, and here's
what we're going to do - let's drag the clustered bar chart directly on top of
our previous analysis. We now see that it has added a new drop zone called cluster
on X set color. We have our graph or our groups set as shared an individual, but
we are looking for prefer. We're going to need to drag that to the y-axis where it
currently says count to change that. Now for the cluster on X-set color, that's
where gender is going to go. We're going to subdivide by gender in the element
properties window; our statistic is mean; that's what we want. Let's display the
error bars confidence interval is 95%, and the bar style is set to bar, click
apply, and ok. We noticed two interesting things in this split bar graph. The first
is that the same pattern emerges for both groups, preference for an individual
clicker was slightly lower among males than among females. Another thing we see
is the error bars for the two groups do overlap. This substantial overlap of the
error bars suggests that males and females do not differ statistically
significantly in their average level of preference. Again, we should do a t-test
in order to make a determination, but the error bars suggest that there is not a
gender difference in clicker preference.