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Showing posts from March, 2014

mathisfun.com's Standard Normal Distribution Table

Now, I am immediately suspicious of a website entitled "MathIsFun" (I prefer the soft sell...like promising teaching aids for statistics that are, say, not awful and boring). That being said, t his app. from mathisfun.com  may be an alternative to going cross-eyed while reading z-tables in order to better understand the normal distribution. mathisfun.com With this little Flash app., you can select z-scores and immediately view the corresponding portion of the normal curve (either from z = 0 to your z, up to a selected z, or to the right of that z). Above, I've selected z = 1.96, and the outlying 2.5% of the curve is highlighted.  Now, this wouldn't work for a paper and pencil exam (so you would probably still need to teach students to read the paper table) but I think this is useful in that it allows students to IMMEDIATELY see how z-scores and portions of the of the curve co-vary. 

Washington Post's "What your beer says about your politics"

Robinson & Feltus, 2014 There appears to be a connection between political affiliation, likelihood to vote, and preferred adult beverage. If you lean right and drink Cabernet Savignon, you are more likely to vote than one who enjoys "any malt liquor" and leans left.  This Washington Post story summarizes data analysis performed by the  National Media Research Planning and Placement . NMRPP got their data from market research firm Scarborough . There is also a video embedded in the Washington Post story that summarizes the main findings. I think this is a good example of illustrating data as well as data mining pre-existing data sets for interesting trends. And beer.

Hall vs. Florida: IQ, the death penalty, and margin of error (edited 5/27/14)

Here is Think Progress' story about a U.S. Supreme Court case that hinges on statistics. The case centers around death row inmate Freddy Lee Hall. He was sentenced to death in Florida for the murder of Karol Hurst in 1978. This isn't in dispute. What is in dispute is whether or not Hall qualifies as mentally retarded and, thus, should be exempt from the death penalty per Virginia vs. Atkins . So, this is an example relevant to any number of psychology classes (developmental, ethics, psychology and the law, etc.). It is relevant to a statistics class because the main thrust of the argument has to do with the margin of error associated with the IQ test that designated Hall as having an IQ of 71. In order to qualify as mentally retarded in Florida, an individual has to have an IQ of 70 or lower. So, at first blush, Hall is out of luck. Until his lawyers bring up the fact that the margin of error on this test is +/- 5 points. This is a good example of confidence intervals/marg...

UPDATE: The Knot's Infographic: The National Average Cost of a Wedding is $28,427

UPDATE: The average cost of a wedding is now $33,391, as of 2017 . Here is the most up to date infographic: Otherwise, my main points from the original version of this survey are still the same: 1) To-be-weds surveyed for this data come were users of a website used to plan/discuss/squee about pending nuptials. So, this isn't a random survey. 2) If you look at the fine print for the survey, the average cost points quoted come from people who paid for a given service. So, if you didn't have a reception band ($0 spent) your data wasn't used to create the average. Which probably leads to inflation of all of these numbers. _________________________________________ Original Post: This infographic describes the costs associated with an "average" wedding. It is a good example non-representative sampling and bending the truth via lies of omission. For the social psychologists in the crowd, this may also provide a good example of persuasion by establishing ...

Nature's "Policy: Twenty tips for interpreting scientific claims" by William J. Sutherland, David Spiegelhalter, & Mark Burgman

This very accessible summary lists the ways people fib with, misrepresent, and overextend data findings. It was written as an attempt to give non-research folk (in particular, law makers), a cheat sheet of things to consider before embracing/rejecting research driven policy and laws. A sound list, covering plenty of statsy topics (p-values, the importance of replication), but what I really like is that they article doesn't criticize the researchers as the source of the problem. It places the onus on each person to properly interpret research findings. This list also emphasizes the importance of data driven change.