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Pew Research Center's "The strong relationship between per capita income and internet access, smartphone ownership"

This finding is super-duper intuitive: A positive, strong correlation exists between national per capita income and rates of internet access and smartphone ownership within that nation. Because it is intuitive, it makes a good example for your class when you teach correlation to your baby statisticians. This graph is  more engaging than your average graph because the good people at Pew made it interactive. You can see which country is represented by which dot. You can also see regional trends as the countries are color-coded by continent/region. For more context and information on this survey, see this more extensive report on the relationship between smartphone/internet access and economic advancement . This report further breaks down technology usage by education level, age, individual income, etc. This data is also useful for demonstrating the distribution of wealth in the world and variability that exists among countries in the same region/on the same continent,

Shameless Self Promotion

Check out my recent publication in Teaching of Psychology. Whomp, whomp!

Kennedy's "'Everybody Stretches' Without Gravity: Mark Kelly Talks About NASA's Twins Study"

In addition to being an astronaut, Scott Kelly is one-half of a pair of twins and a lab rat for NASA researchers studying space travel's effects on the human body. This NPR story details how NASA has been using twin research to learn more about the side-effects of prolonged time in space as the agency prepares to go to Mars. Scott and his twin, Mark (also an astronaut!), have been providing all manner of biodata to researchers. In particular, researchers are interested in the effects of weightlessness and exposure to space radiation on aging. This story provides a good example in class, as you can discuss twin AND longitudinal research. I think you could also use this example to introduce the concept of paired t -tests. UPDATE 2/9/2017: Preliminary research is available if you want to flesh out this example.  MOAR UPDATES 3/3/21: CHECK OUT this PBS documentary featuring the twins! ESPECIALLY useful for a brief class period: This 2-minute clip that describes the twin ...

Granqvist's "Why Science Needs to Publish Negative Results"

This  link  is worth it for these pictures alone: I know, right? Perfect for teaching research methods and explaining the positivity bias in publication. These figures also sum up the reasoning behind the new journal described in this article. New Negatives in Plant Science was founded in order to combat the file drawer problem. It publishes non-significant research. It is open access. It publishes commentaries. It even plans special issues for specific controversial topics within Plant Science. Which absolutely, positively are NOT my jam. However, the creators of this journal hope that it will serve as a model for other fields. Given the recent flare up in the Replication Crisis (now Replication War?), this new journal provides a model for on-going, peer reviewed, replication and debate. I think this journal (or the idea behind this journal) could be used in a research methods class as a discussion piece. Specifically, how else could we reduce the file dra...

Science Friday's "Spot the real hypothesis"

Annie Minoff delves into the sins of ad hoc hypotheses using several examples from evolutionary science (including evolutionary psychology) . I think this is a fun way to introduce this issue in science and explain WHY a hypothesis is important for good research. This article provides three ways of conveying that ad hoc hypotheses are bad science. 1) This video of a speaker lecturing about absurd logic behind ad hoc testing (here, evolutionary explanations for the mid-life "spare tire" that many men struggle with). NOTE: This video is from an annual event at MIT, BAHFest (Bad Ad Hoc Fest) if you want more bad ad hoc hypotheses to share with students. 2) A quiz in which you need to guess which of the ad hoc explanations for an evolutionary finding is the real explanation. 3) A more serious reading to accompany this video is Kerr's HARKing: Hypothesizing after results are known (1998), a comprehensive take down of this practice.

Why range is a lousy measure of variability

Climate change deniers misrepresent data and get called out

 Here is another example of how data visualizations can be accurate AND misleading. I Fucking Love Science broke down a brief Twitter war that started after National Review tweeted the following post in order to argue that global climate change isn't a thing. Note: The y-axis ranged from 110 - -10 degrees Fahrenheit. True, such a temperature range is experienced on planet Earth, but using such an axis distracts from the slow, scary march that is global climate change and doesn't do a very good job of illustrating how discrete changes in temperature map onto increased use of fossil fuels in the increasingly industrialized world. Twitter-verse responded thusly:

Totilo's "Antonin Scalia's landmark defense of violent video games"

A great example using a topic relevant to your students (video games), involving developmental psychology (the effect of violent media on children), and a modern event (Scalia's passing) in order to demonstrate the importance of both research psychology as well as statistics. This article extensively quote Scalia's majority opinion regarding Brown vs. Entertainment Merchants Association, a 2010 U.S. Supreme Court case that decided against California's attempt to regulate the sale of violent video games to minors (the full opinion embedded in the article). Why did Scalia decide against regulating violent video games in the same manner that the government regulates alcohol and cigarette sales? In part, because research and statistics. Of particular use to an instructor of statistics are sections when Scalia cites shaky psychological research and argues that correlational research can not be used to make causal arguments... ...Scalia also discusses effect sizes... ...

Stromberg and Caswell's "Why the Myers-Briggs test is totally meaningless"

Oh, Myers-Briggs Type Indicator, you unkillable scamp. This video , from Vox, gives a concise historical perspective on the scale, describes how popular it still is, and summarizes several of the arguments against the scale. This video explains why the ol' MBTI is not particularly useful. Good for debunking psychology myths and good for explaining reliability (in particular, test-retest reliability) and validity. I like this link in particular because it presents its argument via both video as well as a smartly formatted website. The text in the website includes links to actual peer-reviewed research articles that refute the MBTI.

Davies' "Ted Cruz using firm that harvested data on millions of unwitting Facebook users"

So, this is a story of data mining and Mechanical Turk and data privacy and political campaigns. Lots of good stuff for class discussion about data privacy, applied use of data, etc..  It won't exactly teach your students how to ANOVA, but it is a good and timely discussion piece. Short version of the story: Ted Cruz's campaign hired a consulting firm (Strategic Communications Laboratories, SCL) to gather information about potential voters. They did so by using Amazon's Mechanical Turk to recruit participants. Participants were asked to complete a survey that would give SCL access to your Facebook account. SCL would then download all visible user information from you. And then they would download the same information FROM ALL OF YOUR FRIENDS who did not consent to be involved in the study. Some mTurk users claim this was a violation of Amazon's Terms of Service. This data was then used to create psychological profiles for campaigning purposes. Discussion pieces: ...

Dr. Mages' "APA Exposed: Everything you wanted to know about APA formatting but were afraid to ask."

Teaching undergraduates APA style is not fun. It is not fun for teachers. It is not fun for students. However, I think that the more tools that we, the teachers, have in order to convey the rules of APA style, the more likely we are to find something that finally sticks for our students. This week, I offer one such tool created by Dr. Wendy K. Mages. Dr. Mages created an online, self-paced, free Powerpoint presentation that teaches the essentials of APA style. Lessons are presented in a PowerPoint-esque format with a voice-over (as well as a transcript) I like that Dr. Mages includes some of her own experiences grading students papers in order to keep current students from making frequent mistakes that Dr. Mages has encountered. She also offers plenty of original examples and uses appropriate Powerpoint animations/highlighting to engage the viewer.

Statistics/RM videos from The Economist

TED isn't the only source of videos for teaching statistics . The Economist also makes animated videos that are lousy with data. One easy, no-pay-wall source for such videos is The Economists Videographic playlist on YouTube  (there is a limit on number article views/month at their website ). One really statsy video from The Economist that I've featured previously on this blog explains the real life implications for Type I/Type II error in research (and, specifically, how it leads to errors in published research ). The other videos may not be as directly related to the teaching of statistical topics, but they do illustrate data. Topics range from American union membership trends to this video about world population growth . As you may have inferred from the source, many of these videos focus on national and global economic information, but all of the videos do present data that you can integrate into your classes. Some are more applicable to teaching statistics: This vid...

Explaining between and within group differences using Pew Research data on religion/climate change

I am a big fan of Pew Research Center . They collect, share, and summarize data about a wide variety of topics. In addition to providing very accessible summaries of their findings, they also provide more in-depth information about their data collection techniques, including original materials used in their data collection and very through explanations of their methods. One topic they collect Pew studies is religion and attitudes (religious and secular) held by people of different religions. And it got me thinking that I could use their data in order to explain within and between group differences at the heart of a conceptual understanding of ANOVA. Specifically, Pew gathered data looking at between-group differences in beliefs in global climate change by religion ... Chart created by Pew Research ... and belief in climate change within just Catholics, divided up by political affiliation. Chart created by Pew Research The questionnaires differed slightly for the...