Monday, October 27, 2014

Nell Greenfieldboyce's "Big Data peeks at your medical records to find drug problems"

NPR's Nell Greenfieldboyce (I know, I thought it would be hyphenated as well) reports on Mini-Sentinel, an effort by the government to detect adverse side effects associated with prescription drugs as quickly as possible. Specifically, instead of waiting for doctors to voluntarily report adverse effects, they are mining data from insurance companies in order to detect side effects and illnesses being experienced by people on prescription drugs.

Topics covered by this story that may apply to your teaching:

1) Big data
2) Big data solving health problems
3) Data and privacy issues
4) Conflict of interest
5) An example of the federal government pouring lots of money into statistics to make the world a little safer
6) An example of a data and statistics being used in not-explicitly-statsy-data fields and occupations

Free American Psychological Association style tutorials/quiz

Here are two free, Flash tutorials about APA style directly from APA. The first tutorial is provides an introduction to APA style, while the second provides a list of changes in the 6th edition.

And here is a free quiz on reference alphabetization, also from the APA Style Blog (you can also download the quiz in PDF format for in-class use).

Also, don't forget on these resources (1, 2) for help crafting results sections in APA style.


Monday, October 20, 2014

Quoctrung Bui's "Who's in the office? The American workday in one graph"

Credit: Quoctrung Bui/NPR
Bui, reporting for NPR, shares an interactive graphs that demonstrates when people in different career fields are at the office. Via drop down menus, you can compare the standard work days of a variety of different fields (here, "Food Preparation and Serving" versus "All Jobs").


If you scoff at pretty visualizations and want to sink your teeth into the data yourself, may I suggest the original government report entitled, "American Time Use Survey" or a related publication by Kawaguci, Lee, & Hamermesh, 2013.


Demonstrates: Biomodal data, data distribution, variability, work-life balance, different work shifts.