We need more nonsignificant but readily understood examples in our classes. This correlation/regression example from Information is Beautiful  demonstrates that the calories in delicious caffeinated drinks do not correlate with the calories in the drink. Caffeine has zero calories. The things that make our drinks creamy and sweet may have calories. Easy peasy, readily understood, and this example gives your students a chance to think about and interpret non-significant, itty-bitty effect size findings.  Click here for the data. Aside: Watch your language when using this example. We need calories to stay alive and none of these drinks, in and of themselves, are good or bad. Our students are exposed to way too much of that sort of language and thinking about food and their bodies. What they choose to drink or eat is none of our business. When I share this visual, I omit the information on the far right (exercise) and far left (calorically equivalent foods). It distracts from the...

I'm such a sucker for beer-related statistics examples ( 1 , 2 , 3 ). Here is example 4. Now, I don't know about the rest of you psychologists who teach statistics, but I ALWAYS show the ol' Yerkes-Dodson's graph when explaining that correlation ONLY detects linear relationships but not curvilinear relationships. You know...moderate arousal leads to peak performance. See below: http://wikiofscience.wikidot.com/quasiscience:yerkes-dodson-law BUT NOW: I will be sharing research that finds claims that dementia is associated with NO drinking...and with TOO MUCH drinking...but NOT moderate drinking. So, a parabola that Pearson's correlation would not detect.  https://twitter.com/CNN/status/1024990722028650497

Kristoffer Magnusson is a psychology graduate student with a background in web design and he is using his talents to create succinct, beautiful visualizations of statistical concepts. Below is a screenshot of his interactive tool for a better understanding of correlation and how it relates to shared variance (users can change the n -size and r and watch the corresponding changes in shared variance and the scatter plot). Follow Magnussen's work and statistical visualizations via  @rpsychologist . Special thanks to Randy McCarthy for recommending this resource! Using the "Slide me" bar at the top, you can adjust the correlation in order to visualize the scatter plot, slope, and shared variance.

Triple hilarious with bonus points for being super funny. Damn Avas! Not terribly educational but does illustrate the fact that correlation does not, in fact, equal causation. Property of Bloomberg Businessweek and Vali Chandrasekaran

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... ...

Jess Hagy illustrates her observations about life using simple graphs . I use her illustrations in order to provide examples to my students. Does this illustrate a positive or negative correlation? Property of Jess Hagy Would a correlation detect this relationship? Why or why not?  Property of Jess Hagy According to this diagram, what two different factors may account for the shared variance between the two variables?  Property of Jess Hagy

Gleaned from multiple sources (FB, Pinterest, Twitter, none of these belong to me, etc.). Remember, if your students can explain why a stats funny is funny, they are demonstrating statistical knowledge. I like to ask students to explain the humor in such examples for extra credit points (see below for an example from my FA14 final exam). Using xkcd.com for bonus points/assessing if students understand that correlation =/= causation What are the numerical thresholds for probability?  How does this refer to alpha? What type of error is being described, Type I or Type II? What measure of central tendency is being described? Dilbert: http://search.dilbert.com/comic/Kill%20Anyone Sampling, CLT http://foulmouthedbaker.com/2013/10/03/graphs-belong-on-cakes/ Because control vs. sample, standard deviations, normal curves. Also,"skewed" pun. If you go to the original website , the story behind this cakes has to do w...

If you aren't familiar with cracked.com, it is a website that composes lists. Some are pretty amusing ( 6 Myths About Psychology That Everyone (Wrongly) Believes ,  6 Things Your Body Does Every Day That Science Can't Explain ). An d some are even educational, like "The five most popular ways statistics are used to lie to you" . from cracked.com The list contains good points to encourage critical thinking in your students. Some of the specific points it touches upon: 1) When it is more appropriate to use median than mean. 2) False positives 3) Absolute versus relative changes in amount 4) Probability 5) Correlation does not equal causation And you'll get mad street cred points from undergraduates for using a Cracked list. Trust me.

 I found this Tweet, which leads to a brief report on BBC. A recent report from the World Obesity Federation shows COVID death rates are higher in countries where more than half the population is overweight. Cause and effect, or bad statistics? @TimHarford and @d_spiegel explore - with some maths from me. You can listen on @BBCSounds https://t.co/hevepmz8RC — stuart mcdonald (@ActuaryByDay) March 14, 2021 The BBC has a show called "More or Less," and they explained a recent research finding connecting obesity to COVID 19 deaths.  Here is the original research study . Here is a pop treatment of the original study . For more stats news, you can follow  "More or Less" on Twitter . And they cram, like, a half dozen lessons in this story. It is amazing. I've tried to highlight some of the topics touched upon in this story. How can you use it in class? I think it would be a good final exam question. You could have your students listen to the story, and highlight ...

 Hi, While Blogger does allow me to tag my posts, I thought it might be easier if I just created a compendium for the major sections of Psych Stats? Especially since the search function doesn't work great on mobile devices. And sometimes, you don't want to go poking around and just need to prep for a class fast.  Also, every blessed one of you deserves an Easy Button here in the middle of a pandemic.  And, of course, my mind organizes the world into spreadsheets, so I made a spreadsheet. I hope this helps with your teaching. https://docs.google.com/spreadsheets/d/1b_FcZkJKf5a5M05Jwp62ZJiVYu6s51W2WXve4L8r1MU/edit?usp=sharing PS: Be on the lookout, I'll probably do this for ANOVA, chi-square, regression, correlation, etc.

Crash course website produces brief, informative videos. They are a mix of animation and live action, and cover an array of topics, including statistics. This one is all about measures of central tendency: Here is the listing under their #statistics tag , which includes videos about correlation/causation, data visualization, and variability. And, you know what? This is just a super cool web site, full stop. Here are all of their psychology videos .

Emily Watson, writing for NPR, describes medical research by Ogilvie, vanNiekerk, & Krajden . This research provides a timely, topical example of false positives, false negatives, medical research, and gets your students thinking a bit more flexibly about measurement. This research provides valuable information about debate in medicine: What method of cervical cancer detection is most accurate: The traditional Pap smear, or an HPV screening? The Pap smear works by scraping cells off of a cervix and having a human view and detect abnormal cervical cancer cells. The HPV test, indeed, detects HPV. Since HPV causes 99% of cervical cancers, its presence signals a clinician to perform further screen, usually a colonoscopy. The findings: Women over 30 benefit more from the HPV test. How to use this example in class: - This is a great example of easy-to-follow  research methodology and efficacy testing in medicine. A question existed: Which is better, Pap or HPV test? The questi...

This scale , created by Haidt and Wilson, predicts your political leanings based upon seemingly unrelated questions. Screen grab from time.com You can use this in a classroom to 1) demonstrate interactive, Likert-type scales, 2) face validity (or lack there of). I think this would be 3) useful for a psychometrics class to discuss scale building. Finally, the update at the end of the article mentions 4) both the n-size and the correlation coefficient for their reliability study, allowing you discuss those concepts with students. For more about this research, try yourmorals.org

I have shared Kristoffer Magnusson's fantastic visualizations of statistical concepts here previously ( correlation , Cohen's d ). Here is another one that helps to explain confidence intervals , and how the likelihood of an interval containing true mu varies based on interval size as well as the size of the underlying sample. The site is interactive in two ways. 1) The sliding bar at the top of the page allows you to adjust the size of the confidence interval, which you can read in the portion of the page labeled "CI coverage %" or directly above the CI ticker. See below. 2) You can also change the n-size for the samples the simulation is pulling. The site also reports back the number of samples that include mu and the number of samples that miss mu (wee little example for Type I/Type II error). How to use it in class: Students will see how intervals increase and decrease in size as you reset the CI percentage. As the sample size increases, the range ...

  The unstoppable pop of Taylor Swift (reuters.com) Here are some ideas for using this to teach statistics: Data visualizations and visualization guides: With cats, y'all. And the Taylor Swift handwriting font. I love the whole vibe of this as well as how they explain their data visualizations. Operationalizing things: The page describes three Spotify metrics for music: Acousticness, danceability, and emotion. The data visualization contains a numeric value for each metric and a description of the metric's meaning. DATA!: Okay. This is an excellent example of things already. And it is delightful. Then I thought, "Oh, wouldn't it be fun if this was in spreadsheet form!" (I think that A LOT, friends). But, as I write a book and my syllabi, I don't have time for that,  BUT A REDDITOR DID HAVE TIME FOR THAT . Dr. Doon created a spreadsheet with 18 columns of Spotify data for each son. It doesn't include the Midnights data but is still a fantastic amount of dat...

My friends, winter is coming. Winter in Erie, PA, is no joke, so I've been encouraging my kids to pick up inside hobbies. My youngest is all about flipbooks right now, which inspired me to create my own statsy flipbook: Which, in turn, inspired me to create a blog post about statsy crafts. Crafts that you can do over Winter break for fun or maybe use as assignments for your students? A DIY Christmas gift for your favorite statistician?  The flipbook idea is an easy one to implement, as you only need index cards, a binder clip, and a pencil. Actually, many these can be done on the cheap if you have Legos, paper and pen, a log, yarn, baking supplies around. Not free, but not too expensive, either.  Data visualization via knitting A knitting-data-visualizer tracked temperatures via a knitting project, seen below. The different colors of yarn represent different temperatures on different days. Here is a full article from Gizmodo , which includes a link where you can purchase suppl...

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/

Once again, Kristopher Magnusson has combined is computer programming and statistical knowledge to help illustrate statistical concepts . His latest  interactive tool allows students to view the t-curve for different degrees for freedom. Additionally, students can view error rates associated with different degrees of freedom. Note that the critical region is one-tailed with alpha set at .05. If you cursor around the critical region, you can set the alpha to .025 to better illustrate a two-tailed test (in terms of the critical region at which we declare significance).  Error rates when n < 30 Error rates when n > 30 This isn't the first time Kristopher's interactive tools have been featured on this blog! He has also created websites dedicated to explaining effect size , correlation , and other statistical concepts .

I am absolutely NOT above pandering to undergraduates. For example, I use beer-related examples to illustrate t-test s,   correlation/regression , curvilinear relationships , and data mining/re-purposing . Here is some more. This data was collected to estimate how much more participants would pay for their beer if their beer was created in an environmentally sustainable manner. The answer? $1.30/six pack more. And 59% of respondents said that they would pay more for sustainable beer. NPR talked about it , as well as ways that breweries are going green. Here is a link to the original research . How to use in class: 1) The original research is shared via an open source journal . So, an opportunity to talk about open source research journals. 2) They data was collected via mTurk, another ancillary topics to discuss with your budding research methodologists. 3) The authors of the original study shared their beer survey data ! Analyze to your heart's content. 4) How c...

 Sophie Hill created a great game that shows students how to "eyeball" regression lines (or just lines) by guessing the y-intercept and the slope.  At the beginning of the game, you get a scatter plot. Then, you need to guess the y-intercept and the slope.   Once you make a guess, it will show you the actual line of best fit...and your line, along with residuals and mean squared error. So, this doesn't just allow for eyeballing the regression line but also how to test the fit of a line. P.S.: If you liked this, you'd love the Guess the Correlation game.