In my intro stats class, we discuss shady data practices that aren't lying because they report actual numbers. But they are still shady because good data is presented in such a way as to be misleading or confusing. These topics include: Truncating the y-axis   Collecting measures of central tendency under ideal circumstances Manipulate online ratings (I didn't write the blog post about this yet, but it is coming). Relative vs. Absolute Risk AND HERE IS ANOTHER ONE: Insurance companies were asked to provide price data  RE: the Transparency in Coverage Rule in the Consolidatedated Appropriations Act of 2021. Google that if you want to know more about that, I'm not going into that. Not my lane. That said, it is an appealing idea. Let's have some transparency in our jacked-up healthcare system. And the insurance companies provided the data, but in a way inaccessible to most people. Like, all people, maybe? Because they just splurted out 100 TB of data. So, they totally com...

A database codebook is the documentation of all of the data entry rules and coding schemes used in a given database. And code books usually contain examples of every kind of variable and level of measurement you need to teach your students during the first two weeks of Intro Stats. You can use any code book from any database relevant to your own scholarship as an example in class. Or perhaps you can find a code book particularly relevant to the students or majors you are teaching. Here, I will describe how to use Global Terrorism Database ’s code book  for this purpose. The Global Terrorism Database is housed at the University of Maryland and has been tracking national and international terrorism since 1970 and has collected information on  over 170, 000 attacks. So, the database in and of itself could be useful in class. But, I will focus on just the code book for now, as I think this example cuts across disciplines and interests as all of our students are aware of terroris...

On November 3, 2014, Hyundai and Kia were fined a record-setting $100 million for violating the Clean Air Act. In addition, they were fined for cooking their data and misreporting their fuel economy, using the unethical (cherry-picking) techniques described below by representatives of the federal government: " "One was the use of, not the average data from the tests, but the best data. Two, was testing the cars at the temperature where their fuel economy is best. Three -- using the wrong tire sizes; and four, testing them with a tail wind but then not turning around in the other direction and testing them with a head wind. So I think that speaks to the kinds problems that we saw with Hyundai and Kia that resulted in the mismeasurement." Video and quote from Sam Hirsch, acting assistant attorney general.    Here is EPA's press release about the fine .  How to use it in class: -Hyundai and Kia cherry-picked data, picking out the most flattering data but not the...

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...