Key Points: Chapters 9 & 10

First, some house keeping.

1) Monday is review day. The format will be the same as before where you ask questions of one another. I distributed a review sheet, but also bring your own questions (b/c what’s on the review sheet won’t be on the test!).

2) I will hold office hours after Monday’s lecture. If lots of people show then be prepared to share me or limit your questions. If nobody else shows, then I’m all yours.

Now a recap. The recipe for this week was experiments and content analysis with a dab of validity and a pinch of official stats. Delicious!

Regarding experiments. Knowing the components of experimental design is only the beginning. You also need to understanding how experimental research can be compromised by different threats to internal validity. I also sent additional practice questions for internal validity through Moodle (some are tricky, so pay attention). The difference between laboratory and natural experiments was also emphasized in lecture and tutorial. Ask yourself: How do internal and external validity compare between natural and field experiments? Why does this matter to methodologists? In lecture, I also touched on statistical regression (remember the “smart and dumb babies” example?).

Regarding secondary analysis. Here we focused on content analysis, a non-reactive method for systematically analyzing texts. There are different techniques for coding text (frequency, space, intensity) as well as types of codes (manifest, latent). You had two exercises: one on drug use in film and the other on gender in magazines. There’s no point memorizing specific answers to those exercises because the test will have different examples. Instead, study by applying the process to new examples. For instance, what if you had to conduct a content analysis of “anger” in film? Would you “count” anger using frequency, space, or intensity? What are some examples of manifest vs. latent representations of anger?

Finally, in lecture I talked about the use of existing statistics in secondary analysis. I emphasized the importance of social context in accurately interpreting rates and trends. I distributed a similar review exercise on youth homelessness. It asks you to interpret rates and trends and to speculate about social context. Rates refer to instances at a given moment (e.g., rates of homelessness in 1990) while trends refer to changes over time (e.g., trends in homelessness for different groups over many years). It might help to think of them like cross-sectional and longitudinal time dimensions.

Good luck studying. See you Monday.