Step 1 of Completing your Project

Hi--

When it comes to content analysis, there are two types of information-- manifest and latent. Manifest means that it is readily apparent and latent means that you have to dig a little deeper.

Looking at whether a character on the cover of TV Guide is male, female, monster, etc. is manifest; Determining whether that character is portrayed positively or negatively is latent.

For our class project (which is really just a compendium of individual projects), we're going to analyze a representative sample of TV Guide magazine covers from 1990 through 2014.

How do we do this? Simple.

Let's do this--

Let's do a comparison of a random sample of TV Guide covers from the early 1990s to its last weekly complete year (2013).

(Beginning in 2014, TV Guide published once every 2 weeks instead of once every week).

In fact, let's just make it 1990 and 2013.

Each person will have to code magazine covers from TWO different years to analyze-- one from 1990 and one from 2013.

To select a random sample of magazine covers, we randomly choose a number, let's say "2" and then, beginning with the 2nd issue in 1990, we select every 2nd magazine cover as part of our sample.

Once the year ends, we repeat with the year 2013. This will give us about 26 magazine covers to examine for each year.

Here are a list of possible IVs:

Gender (male, female)
Age (child, young adult, middle age, older adult, senior)
Type of star (TV, movie, music, other, etc.)
Race/Ethnicity (we can simplify and just use the categories "Non-Minority," "Minority"-- otherwise, we open up a whole can of worms trying to figure out who's what...)
Smile (smiling or not smiling)
Year (1990 or 2008)

There are many others, of course, but that gives us a good start.

Possible DVs might include:

Skin exposure (scale of 1 to 5 where 1 is "little to no skin exposure" and 5 is "extreme skin exposure")
Skin color (scale of 1 to 5 where 1 is "light/pale skin" and 5 is "dark skin")
Sexuality (scale of 1 to 5 where 1 is not at all sexual and 5 is extremely sexual)
Smile (smiling or not smiling)
Hair color (scale of 1 to 5 where 1 is dark hair and 5 is blonde/light)
Age (same categories as above)

Any others you can think of...

This is definitely enough to get us going...

So here's what we're going to do. Each of you will complete the following form to help us determine our specific hypotheses.

After we have our hypotheses, we'll need to create the codebook (collectively) so that we know what we mean by each variable we're coding.

Here are two sample codebook items:

Gender: Gender refers to whether the individual(s) on the cover is/are male or female. If they are transgender, code as 3. If they are neither male/female nor transgender (such as a monster or something like that, please code as 999).

Male: 1
Female: 2
Transgender: 3
Other: 999

Age: Age refers to the general perception of where the individual featured on the cover is relative to others in our society. A child actor would be considered "young" and an actor such as Betty White would be considered "senior." Tom Cruise in 1990 might be considered "young adult," but Tom Cruise in 2013 might be considered "middle age."

1. Child
2. Young Adult
3. Middle Age
4. Older Adult
5. Senior

Get it?

So, to get started, here's a sample hypothesis:

TV Guide covers from 2013 are more likely to feature individuals with more skin exposure than those individuals featured on covers from 1990.

In this case, the IV is "year" and the DV is "skin exposure."

My rationale for this hypothesis is that we've become more accepting of skin exposure in mainstream media over the past 25 years. In addition, as more and more media compete, showing more skin might be a way to attract a larger audience, so it makes sense that we might see more skin exposure on today's covers than those covers from two decades ago.

Step 1 of completing your project, then, is to complete the following form and email it to me at jackpowers2@gmail.com.

I want your first hypothesis to have a nominal level of measurement for both the IV and the DV. Why? So that we can check for significance by solving for Chi-Square.

Here it is--

Name:

Hypothesis #1:

• Independent variable:
• Dependent variable:
• Theoretical Rationale:

Statistical test to be used: Chi-Square

For your second hypothesis, I want your IV to be nominal and your DV to be Interval/Ratio. Why? So that we can check for significance by solving for t (t-test).

Hypothesis #2:

• Independent variable:
• Dependent variable:
• Theoretical Rationale:

Statistical test to be used: T-Test

Let me know if you have any questions.

Peace,

Jack