Day 4, Mat115H

• Announcements:
  • Roll
  • RE Sis's on Monmouth:
    • I've contacted Mr. Neikirk about going to Sis's. He thinks it's a great idea, and suggested I contact the current president of the Westside Neighborhood Coalition. I've done so, and am awaiting her response.

    • It seems like the primary concern is getting back in time for a 10:00 class. Another issue is getting there at all (people need rides).

      Tank bus rides: the #11 bus (free!) will get you pretty close. You can walk from 10th and Washington (it's only a couple of blocks). There's a bus from campus at 7:51, which would get you down there at 8:22. So you'd have plenty of time to eat. I'm planning to be down there at 8:00 or so, myself.

      Then there's a bus back to campus from 10th and Washington at 9:59, which I would probably take (gets back by 10:34).

    • I'm checking with Belle about getting a van, however. That might be better. Finally, there's the possibility of personal rides.

• Last time I asked you to consider which of the NKU interventions you want to dig into, to get more information so that we get further guidance on how to proceed. I suggested that you consider these five
  • Psychology and the hope metric (see Prof. Rachel Clark)
  • Nursing and public health surveys in 505.
  • Art and architecture (e.g. sculpture, photography) interventions,
  • Construction (and infrastructure rehabilitation), with Habitat for Humanity.
  • History: check into the history that has been written so far on Westside.
  or any others on the list of NKU "classroom connections" on the handout that I gave you.

  I also said that at least one person will need to check in with psych to see how they measured "hope".

  I'll pass around my copy of that now, and if you'd put your name next to any that you thought that you would like to investigate, I'll collect that and we'll see if we can make some teams to investigate.

• Let's take a (final!) look at the info Mr. Neikirk provided. We started last time, by taking a peek at the fast facts; but we didn't check out the Factfinder stuff, and there's an important reason for doing so:
  • Map of Census Tract 505
  • Fast Facts: Census tract 505
  • American Community Survey 2007-2011, Table S1401

• Today I'm collecting your first official "homework". I'd originally planned to do this as an exercise in class, but we weren't getting to it -- so it became homework! There's a lesson there, somewhere....:)

  Let's talk about what I thought would be the important steps (and see if they make sense to you, based on what you did).

  Steps:

  1. Define terms
  2. Weight variables
  3. Normalize
  4. Define measure (consider deviations from mean, say)
  In particular, let's talk about how the folks who did the research on which What's the Matter With Eastern Kentucky? is based created their metric. If you recall it was based on six measures, and "weighted them equally". How do we do that, when we have six different things? How do we "weight them equally" in a measure?

• Mathematics and Statistics:

  We've begun talking about mathematics (or, more precisely, statistics). We've discussed surveys, and we talked in particular about bias.

  I want to add a few things into the mix today.

  • Surveys:
    • Bias: two kinds that we need to avoid:
      • sampling bias
      • confirmation bias
    • We generally survey to capture the essense of some quantity: we collect data to create a "proxy" or "surrogate", something measurable (but which isn't exactly what we want).

  • Metrics
    • A metric is a measure of something (maybe it's better to think of it as the "measuring stick").
    • The metric is usually a proxy for something else: e.g. schools try to reach certain scores on metrics, to show that they're doing a good job.
    • Changing units in which data are expressed shouldn't change metrics.

  • Measures of central tendency: to illustrate, let's collect heights of you all.
    • arithmetic mean (which we will just call the mean)
    • median

  • Variation: things vary from the center.
    • deviation from the mean/median (sign generally matters!)
      • below average
      • above average

      Do you want to be "below average"? No -- not generally. That's an example of a bias introduced through our use of language, and a preference for a certain directionality in our use of averages.

      Do you want to be below average on "poverty"?

    • "standard deviation"
    • variance
    • outlier: something which fails to fit a pattern;

  • Normalization:
    • We can combine both central tendency and deviation/variation to normalize a variable.
    • This allows us to "weight things equally".

  • Graphical representation
    • graphs and maps give us a better feeling sometimes for how things relate than mere numbers. We'll be playing with a computer tool for representing census data next time (I hope -- I'm trying to arrange for the computer lab for next time).
    • Graphs can be deceiving. We need to be cautious with them. They can also be very powerful.
    • In any event, graphical representation will be a very important complement to our work with numbers from the census bureau.

Some Links:

• A cool tool to allow you to visualize the neighborhood on several census variables by census tract.
  Here's what may be a commercial version of the same thing? It's got a little more resolution. I'm checking with our library to see if we can have the professional access.
• Tract 505 ACS 2006-2010 census Profiles
• Map showing Census Tract 505
• Google Earth map of the tracts of Kentucky (505 is number 27302)
• What's the Matter With Eastern Kentucky?