This may or may not interest my Teaching of Statistics crowd, but I've started a new blog filled with amusing, one-off ideas and examples for teaching Industrial/Organizational Psychology. Like this gem about using data to detect bias in workplace staffing. But in Paw Patrol: I'm teaching it this Spring and have realized that while compiling my own ideas for teaching I/O, I might as well share them with everyone as well. You can find the new blog here .

I am a fan of explaining the heart of a statistical analysis conceptually with words and examples, not with math. Information Is Beautiful has a gorgeous new interactive, Diversity in Tech , that uses data visualization to present gender and ethnic representation among employees at various big-name internet firms. I think this example explains why we might use Chi-Square Goodness of Fit. I think it could also be used in an I-O class. So, what this interactive gives you is a list of the main, big online firms. And then the proportions of different sort of people who fall into each category. See below: When I look at that US Population baseline information, I see a bunch of expected data. And then when I see the data for different firms, I see Observed data. So, I see a bunch of conceptual examples for chi-square Goodness of Fit. For example, look at gender. 51% of the population is female. That is you Expected data. Compare that to data for Indiegogo. They have 50% female e...

Our World in Data is an impressive, creative-commons licensed site managed by Max Roser . And it lives up to its name. The website provides all kinds of international data, divided by country, topic (population, health, food, growth & inequality, work, and life, etc.), and, when available, year. It contains its own proprietary data visualizations, which typically feature international data for a topic. You can customize these visualizations by nation. You can also DOWNLOAD THE DATA that has been visualized for use in the classroom. Much of the data can be visualized as a map and progress, year by year, through the data, like this data on international human rights. https://ourworldindata.org/human-rights/  https://ourworldindata.org/human-rights/ There are also plenty of topics of interest to psychologists who aren't teaching statistics. For example, international data on suicide: Data for psychology courses...https://ourworldindata.org/suicide/ Work...

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. ...

Data USA draws upon various federal data sources in order to generate visualizations about cities and occupations in the US. And it provides lots of good examples of simple, descriptive statistics and data visualizations. This website is highly interactive and you can query information about any municipality in the US. This creates relevant, customized examples for your class. You can present examples of descriptive statistics using the town or city in which your college/university/high school is located or you could encourage students to look up their own hometowns. Data provided includes job trends, crime, health care, commuting times, car ownership rates...in short, all sorts of data. Below I have included some screen shots for data about Erie, PA, home of Gannon University: The background photo here is from the Presque Isle, a very popular state park in Erie, PA. And, look, medians!

This story describes an 1) an efficacy study that 2) touches on some I/O/Health psychology research and 3) has gained the unwanted attention of government regulatory agencies charged with protecting research participants.   The study described in this story is an efficacy study that questions a decision made by the 2003 Accreditation Council for Graduate Medical Education. Specifically, this decision capped the number of hours that first-year medical student can work at 80/week and a maximum shift of 16 hours. The PIs want to test whether or not these limits improve resident performance and patient safety. They are doing so by assigning medical students to either 16-hour maximum shifts or 30-hour maximum shifts. However, the research participants didn't have the option to opt out of this research. Hence, an investigation by the federal government. So, this is interesting and relevant to the teaching of statistics, research methods, I/O, and health psychology for a numbe...

Weber and Silverman's article for the Wall Street Journal has lots of good psychy/stats information  ( here is a .pdf of the article if you hit a pay wall ). I think it would also be applicable to health and I/O psychology classes. The graph below summarizes the main point of the article: Certain occupations have a greater likelihood of obesity than others (a good example of means, descriptive statistics, graphs to demonstrate variation from the mean). As such, how can employers go about increasing employee wellness? How does this benefit an organization financially? Can data help an employer decide upon where to focus wellness efforts? The article goes on to highlight various programs implemented by employers in order to increase employee health (including efficacy studies to test the effectiveness of the programs). In addition to the efficacy research example, the article describes how some employers are using various apps in order to collect data about employee health and...

UPDATE: The link listed below is currently not working. I've talked to Ariana Giorgi about this, and she is working to get her graph up and running again via Bloomberg. She was kind enough to provide me with a provide me with alternate URLs to the interactive scatter plot  as well as a link to the original text of the story . Ariana is doing a lot of interesting work with data visualizations, follow her on Twitter or hit up her website . _______________________________________________________________________________ This scatter plot (and accompanying news story from Bloomberg News)  demonstrates what a non-existent linear relationship looks like. The data plots CEO pay on the x-axis and stock market return for that CEO's organization on the y-axis. I could see where this graph would also be useful in an I/O course in discussions of (wildly unfair) compensation, organizational justice, etc. http://www.bloomberg.com/bw/articles/2014-07-22/for-ceos-correlation...

Credit: Quoctrung Bui/NPR Bui, reporting for NPR, shares  interactive graphs that demonstrate when people in different career fields are at the office. Via drop-down menus, you can compare the standard workdays of a variety of different fields (here, "Food Preparation and Serving" versus "All Jobs"). If you scoff at pretty visualizations and want to sink your teeth into the data yourself, may I suggest the original government report entitled, " American Time Use Survey " or a related publication by Kawaguci, Lee, & Hamermesh, 2013 . Demonstrates: Biomodal data, data distribution, variability, work-life balance, different work shifts.

Yelp distribution visualization, posted by redditor minimaxir This data distribution example comes from the subreddit r/dataisbeautiful  (more on what a reddit is  here ). This specific posting (started by minimaxir) was prompted by several  histograms illustrating  customer ratings for various Yelp (customer review website) business categories as well as the lively reddit discussion in which users attempt to explain why different categories of services have such different distribution shapes  and means. At a basic level, you can use this data to illustrate skew, histograms, and normal distribution. As a more advanced critical thinking activity, you could challenge your students to think of reasons that some data, like auto repair, is skewed. From a psychometric or industrial/organizational psychology perspective, you could describe how customers use rating scales and whether or not people really understand what average is when providing customer feedba...