Positive, interactive linear relationships, y'all. Chase, of Overflow Data , created a scatter plot that finds that as income goes up, so does rent. Pretty intuitive, right? I think intuitive examples are good for students. Cursor over the dots to see what metro area each dot represents, or use the search function to find your locale and personalize the lesson a wee bit for your students.

Robert Grant's website Draw My Data  provides you with a blank scatter plot graph. You add your dots, and the website generates M and SD for your X and Y, as well as r for the relationship between X and Y. It even generates a data set for download. My Twitter handle, @notawful, has an r of -.485. Via http://robertgrantstats.co.uk/drawmydata.html Great for illustrating a specific kind of relationship (positive, negative, etc.) to your students. Also allows for much goofiness, like Alberto Cairo, who plotted a T-rex and went viral. And then the T-rex plot, and a bunch of other plots, were used to create an animated, updated version of Anscombe's Quartet . And that was presented at a conference by Matejka & Fitzmaurice. https://www.autodeskresearch.com/publications/samestats So, lots of stats goodness here. You can let your students play with Draw Your Data or use that website to generate data sets for use in class. You can also use the dino data to illustr...

This is a lot of I/O and personality a little bit of stats. But it does demonstrate correlation and percentiles, and it is interactive. For this article  from Time, Johnson and Wilson used participant scores on a very popular vocational selection tool, the Holland Inventory (sometimes called the RAISEC), and participant salary information to see if there is a strong relationship between salary and personality-job fit. There is not. How to use in class: -Show your students what a weak correlation looks like when expressed via scatter plot. Seriously. I spend a lot of time looking for examples for teaching statistics. And there are all sorts of significant positive and negative correlation examples out there . But good examples of non-relationships are a lot rarer. -If you teach I/O, this fits nicely into personality-job fit lecture. If you don't teach I/O but are a psychologist, this still applies to your field and may introduce your students to the field of I/O. ...

Sometimes, we need to convince our students that taking a statistics class changes the way they think for the better. This example demonstrates that one seemingly simple skill, interpreting a scatter plot, is tougher than it seems. Pew Research conducted a survey on scientific thinking in America ( here is a link to that survey ) and they found that only 63% of American adults can correctly interpret the linear relationship illustrated in the scatter plot below. And that 63% came out a survey with multiple-choice responses! How to use in class: -Show your students that a major data collection/survey firm decided that interpreting statistics was an appropriate question on their ten-item quiz of scientific literacy. -Show your students that many randomly selected Americans can't interpret a scatter plot correctly. And for us instructors: -Maybe a seemingly simple task like the one in this survey isn't as intuitive as we think it is!

UPDATE, 9/22/22: Here is a non-paywalled link to this information:  https://www.nytimes.com/2017/10/09/learning/whats-going-on-in-this-graph-oct-10-2017.html This article from the NYT is based on a survey . That survey asked a bunch of nutritionists if they considered certain foods healthy. Then they asked a bunch of everyday folks if they considered the same foods to be healthy. Then they generated the percentage of each group that considered the food healthy. And the NYT put the nutritionist responses on a Y-axis, and commoners on the X, and made a lovely scatterplot... Nutritionists and non-nutritionists agree that chocolate chip cookies are not healthy. However, nutritionists are far more critical of American cheese than are non-nutritionists.  ...and provided us with the raw data as well.

Jethro Waters, Dan Peterson, Ph.D., Laurie McCollough, and Luke Norton made a pair of animated videos ( 1 , 2 ) that explain why correlation does not equal causation and how we can perform lab research in order to determine if causal relationships exist. I like them a bunch. Specific points worth liking: -Illustrations of scatter plots for significant and non-significant relationships. Data does not support the old wive's tale that everyone goes a little crazy during full moons. -Explains the Third Variable problem. Simple, pretty illustration of the perennial correlation example of ice cream sales (X):death by drowning (Y) relationship, and the third variable, hot weather (Z) that drives the relationship. -In addition to discussing correlation =/= causation, the video makes suggestions for studying a correlational relationship via more rigorous research methods (here violent video games:violent behavior). Video games (X) influence aggression (Y) via the moderato...

I take credit for none of these. A few have been posted here before. by Rayomond Biesinger, http://fifteen.ca/ Creator unknown, usually attributed to clipart? http://www.sciencemag.org/content/331/6018.cover-expansion https://www.flickr.com/photos/lendingmemo/ https://lovestats.wordpress.com/2014/11/10/why-do-kids-and-you-need-to-learn-statistics-mrx/ http://memecollection.net/dmx-statistics/ 9/23/15 Psychometrics: Interval scale with proper anchors 2/9/16 4/19/16 4/28/16 "Symbols that math urgently needs to adopt" https://mathwithbaddrawings.com/2016/04/27/symbols-that-math-urgently-needs-to-adopt/ http://www.mrlovenstein.com/ http://www.smbc-comics.com/ 9/8/16 2/9/2107 https://hbr.org/2017/02/if-you-want-to-motivate-employees-stop-trusting-your-instincts https://www.theguardian.com/politics/2017/jan/19/crisis-of-statistics-big-data-democracy?CMP=share_btn_tw 2/13/17 ...