In PSY 2401 (basic statistics for psychology), I’ve been offering the students surveys to let me (and each other) know how they perceived the homework assignments. So far, I only have one dataset–homework #1. I have learned a few things, the first of which is that Blackboard is not a user-friendly (or terribly useful) way to deliver surveys. Not its strong suit, so to speak. Other things I’ve learned are below:
Age: No surprises here.
Mostly traditional students.
Sex: This is how it is in psychology.
I’ve been trying to get some graphs prepared from the Knowledge & Attitudes data from Fall 2012 (K&A 2012). One of our chunks of data was a series of questions given to survey respondents about their views of the immorality and probable harm caused by various sexual situations (I call these the scenarios): each scenario specified an initiator, a recipient (for lack of a better term), and the age (15 or 21) and sex of each. The initiator was described as “starting a sexual relationship” with the recipient. They always engaged in the same activities: kissing and touching each other’s genitals. There are a lot of variables. Here’s one way to look at them:
- Initiator sex
- Initiator age (2 levels: 15 or 21 years old)
- Recipient sex
- Recipient age (15 or 21)
- Immorality rating (DV)
- Harm rating (DV)
To make things slightly more complex, I simplified the survey forms by cutting out some of the potential crossings of the variables: initiator and perpetrator sex are fully crossed (M/M, M/F, F/M, and F/F conditions) but the ages aren’t–15-year-old initiators are always paired with 21-year-old recipients, and vice-versa. For analysis (but possibly not graphing) purposes it’s also important to know that some comparisons happened between subjects (there were two more-or-less randomly-assigned forms) and others within subjects, with the order of presentation (sadly) fixed. In the future I may do this with more rigorous crossing of all the variables.
I could present subsets of variables in graphs, but I’m really interested in getting as many (independent) variables as possible represented in a single chart, not least because I expect higher-order interactions, and only showing a few variables might obscure those or even mislead the viewer. Here’s an initial stab with only some of the variables: