Data has been used to learn a bit more about the age old observation that books are always better than the movies they inspire. Fivethirtyeight writer Walk Hickey gets down to the brass tacks of this relationship by exploring linear relationships between book ratings and movie ratings.  The biggest discrepancies between movie and book ratings were for "meh" books made into beloved movies (see "Apocalypse Now"). How to use in class: -Hickey goes into detail about his methodology and use of archival data. The movie ratings came from Metacritic, the book ratings came for Goodreads. -He cites previous research that cautions against putting too much weight into Metacritic and Good reads. Have your students discuss the fact that Metacritic data is coming from professional movie reviewers and Goodreads ratings can be created by anyone. How might this effect ratings? -He transforms his data into z-scores. -The films that have the biggest movie:book rati...

The writer helped out a PhD candidate by participating in his research, and then described the research process for io9.com readers . I like this because it is describes the research process purely from the perspective of the research participant who doesn't know what the exact hypothesis is. This could be useful for explaining what research participation is like for introductory students. You could used it in a methods class by asking the students to figure out why they used the procedures that they did, and what procedures and scales she describes in her narrative. She describes the informed consent, a personality scale (what do you think the personality scale was trying to assess?), and rating stimuli in two ways (brain scan as well as paper and pencil assessment...why do you think they needed both?) Details to Like: -She is participating is psychology research (neruo. work that may benefit those with PTSD someday) -She describes what is entailed when wearing an elect...

Found this gem, "Guess the Correlation" , via the subreddit r/statistics . The redditor who posted this resource (ow241) appears to be the creator of the website. Essentially, you view different scatter plots and try to guess r . Points are rewarded or taken away based on how close you are to true  r . The game tallies your average amount of error as well. It is way more addictive than it sounds. I think that accuracy increases with time and experience. True r for this one was .49. I guess .43, which isn't so bad. I think this is a good way for statistics instructors to procrastinate. I think it is also a good way to help your students build a more intuitive ability to read scatter plots and predict the strength of linear relationships.

If you haven't already, please consider joining Teaching of Psychology  (Division 2 of APA). Your membership fees help fund plenty of great initiatives, including: Teaching Statistics and Research Methods: Tips from TOP by Jackson & Grigs This free e-book is a compilation of scholarship of teaching publications. Office of Teaching Resources in Psychology's (OTRP) Teaching Resources This page is divided by topical area in psychology (including Statistics) and includes instructional resources for every topic. Most of the material was created as part of OTRP's Instructional Resource Reward. Among the useful resources are a free booklet containing statistics exercises in both SPSS and R as well as an intense primer on factorial research design . UPDATE (2/24/16): This new resource provides a number of hands-on activities to demonstrate/generate data for all of the concepts typically taught in intro statistics.   Project Syllabus  Project Syllabus is a colle...

If you are unaware, Noba Project is a collaboration of many, many psychology instructors who create and make freely available text books as well as stand-alone chapters (modules) that cover a wide variety of psychology topics. You can build a personalized text book AND access test banks/powerpoints for the materials offered. Well, one of the new modules covers the replication crisis in psychology . I think it is thorough treatment of the issue and appropriate for undegraduates.

EDIT: All of this content appears to have been removed from NFL.com. If anyone has any luck finding it, please email me at hartnett004@gannon.edu The NFL and the statistics folks over at Freakonomics got together and made some...learning modules? Let's call them learning modules. They are interactive websites that teach users about very specific questions related to football (like home field advantage , instances when football player statistics don't tell the whole story about a player/team , whether or not firing a head coach improves a failing team , the effects of player injury on team success , etc.) and then answer these questions via statistics. Most of the modules include interactive tables, data, and videos (featuring the authors of Freakanomics) in order to delve into the issue at hand. For example: The Home Field Advantage : This module features a video, as well as a interesting interactive map that illustrates data about the exact sleep lost experienced by ...

This news story discusses medical advice regarding dates for recommended annual mammograms for women. Of particular interest for readers of this blog: Recommendations for regular mammograms are moving later and later in life. Because of the very high false positive rate associated with mammograms and subsequent breast tissue biopsies. However, women who have a higher probability (think genetics) are still being advised to have their mammograms earlier in life. Part of the reason that these changes are being made is because previous recommendations (start mammograms at 40) were based on data that was 30-40 years old ( efficacy studies/replication are good things!). Also, I generally love counter-intuitive research findings: I think they make a strong argument for why research and data analysis are so very important. I have blogged about this topic before. This piece by Christy Ashwanden  contains some nice graphs and charts that demonstrate that enthusiastic preventative care ...

Hi, I wanted to post a blog about a job opportunity that available in my department here at Gannon University . Currently, we are seeking a tenure-track assistant professor who specializes in clinical or counseling psychology and would be interested in teaching theories of personality, psychological assessment, and other specialty undergraduate courses. Gannon is a true undergraduate institution. We teach a 4/4 course load, typically with two and sometimes three unique teaching preps. I started at Gannon in 2009. In that time, I've received $1000s of dollar in internal grant funding to pursue my work in the scholarship of teaching. In addition to supporting the scholarship of teaching, Gannon provides internal support so that faculty can create global education opportunities as well as service learning opportunities for our students. For instance, one of my colleagues is currently writing a proposal for a History of Psychology class that would include an educational trip to E...

Tovia Smith filed a report with NPR that detailed the psychometric delicacies of trying to measure the sexual assault rates on a college campus. I think this story is highly relevant to college students. I also think it also provides an example of the challenge of operationalizing variables as well as self-selection bias. This story describes sexual assault data collected at two different universities, Rutgers and U. Kentucky. The universities used different surveys, had very different participation rates, and had very different findings (20% of Rutgers students met the criteria for sexual assault, while only 5% of Kentucky students did). Why the big differences? 1) At Rutgers, students where paid for their participation and 30% of all students completed the survey. At U. Kentucky, student participation was mandatory and no compensation was given. Sampling techniques were very different, which opens the floor to student discussion about what this might mean for the results. Who m...

This article describes how the Pennsylvania Department of Corrections is using risk assessment data in order to predict recidivism, with the hope of using such data in order to guide parole decisions in the future. So, using data to predict the future is very statsy, demonstrates multivariate modeling, and a good example for class, full stop. However, this article also contains a cool interactive tool, entitled "Who Should Get Parole?" that you could use in class. It demonstrates how increasing/decreasing alpha and beta changes the likelihood of committing Type I and Type II errors. The tool allows users to manipulate the amount of risk they are willing to accept when making parole decisions. As you change the working definition of a "low" or "high" risk prisoner, a visualization will startup, and it shows you whether your parolees stay out of prison or come back. From a statistical perspective, users can adjust the definition of a low, medium, and h...

I love my fellow Reddit data geeks over at r/dataisbeautiful . Redditor faux_pseudo created a frequency chart of the deliciousness found in a box of Cracker Jacks. I think it would be funny to ask students to discuss why this graph is misleading (since the units are of different size and the pop corn is divided into three columns). You could also discuss why a relative frequency chart might provide a better description. Finally, you could also replicate this in class with Cracker Jacks (one box is an insufficient n-size, after all) or try it using individual servings of Trail Mix or Chex Mix or order to recreate this with a smaller, more manageable sample size. Also, as always, Reddit delivers in the Comments section:

Math with Bad Drawings is a very accurately entitled blog. Math teacher Ben Orlin illustrates math principles, which means that he occasionally illustrates statistical principles. He dedicated one blog posting to probability, and what probability means in different contexts. He starts out with a fairly standard and reasonable interpretation of p :  Then he has some fun. The example below illustrates the gap that can exist between reality and reporting. And then how philosophers handle probability (with high- p statements being "true"). And in honor of the current Star Wars frenzy: And finally...one of Orlin's Twitter followers, JP de Ruiter , came up with this gem about p -values:

Statistics aficionados over at FiveThirtyEight applied statistics (specifically, tools used by epidemiologists) to the Summer of 2015  outbreak of Legionnaires' Disease  in New York. This story can be specifically used in class as a way of discussing how simple bar graphs can be modified as to display important information about the spread of disease. This news story also includes a link to a learning module  from the CDC. It takes the user through the process of creating an Epi curve. Slides 1-8 describe the creation of the curve, and slides 9-14 ask questions and provide interactive feedback that reinforces the lesson about creating Epi curves. Graphs are useful for conveying data, but even one of our out staples, the bar graph, can be specialized as they share information about the way that disease spread. 1) Demonstrates statistics being used in a field that isn't explicitly statistics-y. 2) A little course online via the CDC for your students to learn to...