Slate's The Littlest Tasters More research methods than statistics, this article describes the difficulty in determining taste preferences in wee humans who don't speak well if at all. slate.com The goods for teaching: They mention the FACE scale. The research methods described go beyond marketing research and this could be useful in a Developmental class to describe approaches used in data collection for children (like asking parents to rate their children's reactions to foods). I've used this as a discussion board prompt when discussing research ethics, both for simply conducting research with children as well as the ethics of marketing (not so healthy foods) towards children. Aside: They also describe why kids like Lunchables, which has always been a mystery to me. Apparently, kids are picky about texture and flavor but they haven't developed a preference for certain foods to be hot or cold. The Huffington Post's " You'll Never Look at ...

Tyler Vigen has has created  a long list of easy-to-paste-into-a-powerpoint graphs that illustrate that correlation does not equal causation. For instance, while per capita consumption of cheese and number of people who die by become tangled in their bed sheets may have a strong relationship (r = 0.947091), no one is saying that cheese consumption leads to bed sheet-related death. Although, you could pose The Third Variable question to your students for some of these relationships). Property of Tyler Vigens, http://i.imgur.com/OfQYQW8.png Vigen has also provided a menu of frequently used variables (deaths by tripping, sunlight by state) to help you look for specific examples. This portion is interactive, as you and your students can generate your own graphs. Below, I generated a graph of marriage rates in Pennsylvania and consumption of high fructose corn syrup. Generated at http://www.tylervigen.com/

a) The addition of this post means that I now have TWO Snoop Dogg blogg labels  for this blog. b) Daniels' graph allows students to see archival data (and research decisions used when deciding how to analyze the archival data as well as content analysis) in order to determine which rapper has the largest vocabulary. Here is Matthew Daniels interactive chart detailing the vocabularies of numerous, prominent rappers. Daniels sampled each musician's first 35,000 lyrics for the number of unique words present. He went with 35,000 in order to compare more established artists to more recent artists who have published fewer songs. (The appropriateness of this decision could be a source of debate in a research methods class.) Additionally, derivatives of the same word are counted uniquely (pimps, pimp, pimping, and pimpin count as four words). This decision was guided, from what I can gather, by the time of content analysis performed. Property of Matthew Daniels...note: The ori...