This blog posting by Dr. Randy McCarthy discusses best practices in organizing/naming conventions for data files. These suggestions are probably more applicable to teaching graduate students than undergraduates. They are also the sorts of tips and tricks we use in practice but rarely teach in the classroom (but maybe we should). Included in Randy's recommendations: 1) Maintain consistent naming conventions for frequently used variables (like scale items or compiled scales that you use over and over again in your research). Then create and run the same syntax for this data for the rest of your scholarly career. If you are very, very consistent in the scales you use and the data analyses your run, you can save yourself time by showing a little forethought. 2) Keep and guard a raw version of all data sets. 3) Annotate your syntax. I would change that to HEAVILY annotate your syntax. I even put the dates upon which I write code so I can follow my own logic if I have to let a d...

This semester (SP 15), I taught an Honors section of Psychological Statistics for the first time. In this class, I decided to take my students to a minor league baseball game ( The Erie Seawolves , the Detroit Tiger's AA affiliate) in order to teach my students a bit about 1) applied statistics and data collection as well as 2) selecting the proper operationalized variable when answering a research question. Students prepared for the game day activity via a homework assignment they completed prior to the game. For this assignment, students learned about a few basic baseball statistics (batting average (AVG), slugging (SLG), and on-base plus slugging (OPS)). They looked up these statistics for a random Seawolves' player (based on 2014 data) and learned out to interpret these data points. They also read an opinion piece on why batting averages are not the most informative piece of data when trying to determine the merit of a given player. The opinion piece tied this exe...

As created by Jess Hartnett.

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I am busy prepping my statistics class for the fall (as well as doing a bunch of stuff that I should have done in June, but I digress). Most of my students are required to take statistics and are afraid of mathematics so I'm going to try to convince them to embrace statistics by showing them that more and more non-statsy jobs require data collection, data analysis, data driven decisions, program assessment, etc..  I find that my students are increasingly aware of the current job market as well as their student loan debt. As such, I think that students are receptive to arguments that  explain  how even a little bit of statistical knowledge can make them more attractive to potential employers. Here are some resources I have found to do just that.  This article by Susan Adams for Forbes lists the top ten skills employers are looking for in employees. Included in the top ten: "2. Ability to make decisions and solve problems 5. Ability to obtain and ...

Here are two articles, one from The Observer and one from Perspectives on Psychological Science . The PPS article, by Chew and Dillion, is a call for more research to study statistics anxiety in the classroom. Chew and Dillon provide a thorough review of statistics anxiety research, with a focus on antecedents of anxiety as well as interventions (The Observer article is a quick summary of those interventions) and directions for further research. I think Chew and Dillion make a good case for why we should care about statistics anxiety as statistics instructors. As a psychologist who teaches statistics, I find that many of my students are not in math-related majors but can still learn to think like a statistician, in order to improve their critical thinking skills and prepare them for a data/analytic driven world after graduation. However, their free-standing anxiety related to simply being in a statistics class is a big barrier to this and I welcome their suggestions regarding the re...