we try to measure the most fluid paradigm in the
world–human thought.
ANALYSIS OF SURVEYS
Learning Objective:
Analyze and use the data
generated by audience surveys.
The simplest and easiest way to communicate a
complicated list of data to an audience is with a picture.
As journalists and as a result of your studying Chapter
6 of this training manual, you already know about the
various types of visual communication possible for
displaying data. The final section in this chapter covers
understanding the survey data you have collected and
how to correctly plug that data into visual repre-
sentations, such as graphs and charts.
CORRELATIONS
As mentioned earlier in this chapter, making
decisions, based on samples of under 400 from general
populations of 4,000 or less, is possible and reliable if
you are making simple comparisons. A simple
comparison is what percentage of your sample watches
television. Your results might look like the following:
34 percent–0600-0800, 10 percent–0801-1000, and so
on. But if you wanted to know what percentage of those
who watch from 0600-0800 are women or children, then
remember, you must have a large enough sample to keep
each category you want your survey broken into over
100. This will keep the relationship between viewers
watching from 0600-0800 and the sex of those viewers
reliable.
Correlating viewership with demographics is
important, for example, when you plan to run
information spots targeting women. Questions, such as,
when do most spouses watch your television station,
listen to your radio station or what editions of your paper
are they more likely to read, are important to answer
when you plan an information campaign. Know Your
Audience. As Rear Adm. Baker, the former CHINFO
once said: “Work smarter, not harder.”
GRAPHIC DISPLAY
The last section of this chapter ties back with the
scenario used in the introduction. Putting your data into
a picture to give it impact is absolutely necessary and
also dangerous. It is necessary because few people will
take the time to study raw print-out sheets of data, no
matter what the claims of the surveyor are. It is also
dangerous because a mistake in how you present your
survey findings can ruin the credibility of all your
efforts.
How many times have you heard the saying,
“Statistics lie”? You must display your survey findings
in the most understandable way possible and still stay
within the boundaries of fair representation. Perhaps the
best way to understand how to present your data fairly
is to see some examples of how to be unfair. These
examples will also increase your ability to spot abuse of
statistical data.
Let us say that as the command’s expert on survey
techniques, you volunteered to supervise Morale,
Welfare, and Recreation’s facility usage survey. You
have followed the guidelines in this chapter and have
collected reliable and valid data and are ready to present
the results to the CO.
The CO’s pet project is the base racquetball courts,
and he is interested to see how many sailors are using it
since it was built last year. You are aware of his interest
and decide to graph the informal aggregate data
collected by reviewing the sign-up sheets in the
racquetball court front office. You hope to show a steady
increase in usage since your broadcasting outlet has
been regularly producing information and selling spots
on the new courts. Starting with January, you list each
month on the bottom of your line graph. On the left, you
place numbers of users in blocks of 20 and begin to place
your data on the graph. An example of this is shown in
figure 9-5.
The line chart does indeed show a steady
progression of increased usage up the graph. However,
because of the scale you used, the data does not really
jump out at you. So you decide to display your
information in a more effective manner. To be more
pleasing to the eye, you cut off the upper and lower
sections of the graph to end up with the display shown
in figure 9-6.
The graph looks better to you now and it even shows
the slight dip in the summer months when you were
forced to go TAD causing, in your estimation, radio spot
production to fall off. If only the data could illuminate
that fact a bit more you might even get a letter of
appreciation from the CO for doing such a good job of
promoting his pet project. To highlight the summer dip,
you decide to go with the graph in figure 9-7.
That does it. Who could deny that the base
racquetball court, the CO’s pet enterprise and your
personal advertising project, is not a big success? Was
the data changed in the various graphs? Was there a lie
in any of the charts? The answer is yes and no. There is
9-10
