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u/zonination's "Got ticked off about skittles posts, so I decided to make a proper analysis for /r/dataisbeautiful [OC]"

The subreddit s/dataisbeautiful was inundated by folks creating color distributions for bags of candy. And because 1) it is Reddit and 2) stats nerds take joy in silly things, candy graphing got out of hand. See below: https://www.reddit.com/r/dataisbeautiful/comments/5bojxl/oc_the_data_suggests_that_certain_colors_are_not/ https://www.reddit.com/r/dataisbeautiful/comments/5bmo3a/color_distribution_of_one_more_partysized_bag_of/ https://www.reddit.com/r/dataisbeautiful/comments/5cmemr/a_pie_chart_of_mm_colors_from_a_single_500g_bag_oc/ And because it is Reddit, and, to be a fair, statistically unreliable, other posters would claim that this data WASN'T beautiful because it was a small sample size and didn't generalize. One bag of Skittles, they claimed. didn't tell you a lot about the underlying population of Skittles. Until Redditor zonination came along, bought 35 enormous bags of Skittles, and meticulously documented the color distribution in each ...

Kevin McIntyre's Open Stats Lab

Dr. Kevin McIntryre from Trinity University has created the Open Stats Lab.  OSL provides users with research articles, data sets, and worksheets for studies that illustrate statistical tests commonly taught in Introduction to Statistics. Topics covered, illustrated beautifully by Natalie Perez All of his examples come from Open Science Framework-compliant publications from Psychological Science. McIntyre presents the OSF data (in SPSS, R, and .  CSV files are available ), the original research article, AND a worksheet to accompany each article. Layout for each article/data set/activity. This article demonstrates one-way ANOVA. I know. It can be challenging to find 1) research an UG can follow that 2) contains simple data analyses. And here, McIntryre presents it all. This project was funded by a grant from APS.

A wintery mix of holiday data.

Property of  @JenSacco54 http://www.huffingtonpost.com/entry/mariah-carey-christmas_us_561f989be4b0c5a1ce621a69 A wintery example of why range is a crap measure of variability http://qz.com/859303/americas-most-common-christmas-related-injuries-in-charts/

Wilson's "Find Out What Your British Name Would Be"

Students love personalized, interactive stuff.  This website from Chirs Wilson over at Time allows your American students to enter their name and they recieve their British statistical doppleganger name in return. Or vice versa. And by statistical doppleganger, I mean that the author sorted through name popularity databases in the UK and America. He then used a Least Squared Error model in order to find strong linear relationships for popularity over time between names. How to use in class: Linear relationship LSE Trends over time

Aschwanden's "You Can’t Trust What You Read About Nutrition"

Fivethirtyeight provides lots of beautiful pictures of spurious correlations found by their own in-house study. At the heart of this article are the limitations of a major tool use in nutritional research, the Food Frequency Questionnaire (FFQ). The author does a mini-study, enlisting the help of several co-workers and fivethirtyeight.com readers. They track track their own food for a week and reflect on how difficult it is to properly estimate and recall food (perhaps a mini-experiment you could do with your own students?). And she shares the spurious correlations she found in her own mini-research: Aschwanden also discusses how much noise and lack of consensus their is in real, published nutritional research (a good argument for why we need replication!):  http://fivethirtyeight.com/features/you-cant-trust-what-you-read-about-nutrition/ How to use in class: -Short comings of survey research, especially survey research that relies on accurate memories -...

Teaching the "new statistics": A call for materials (and sharing said materials!)

This blog is usually dedicated to sharing ideas for teaching statistics. And I will share some ideas for teaching. But I'm also asking you to share YOUR ideas for teaching statistics. Specifically, your ideas for teaching the new statistics: effect size, confidence intervals, etc. The following email recently came across the Society for the Teaching of Psychology listserv from Robert Calin-Jageman (rcalinjageman@dom.edu). "Is anyone out there incorporating the "New Statistics" (estimation, confidence intervals, meta-analysis) into their stats/methods sequence? I'm working with Geoff Cumming on putting together an APS 2017 symposium proposal on teaching the New Statistics.  We'd love to hear back from anyone who has already started or is about to.  Specifically, we'd love to:         * Collect resources you'd be willing to share (syllabi, assignments, etc.)         * Collect narratives of your experi...

Chokshi's "How Much Weed Is in a Joint? Pot Experts Have a New Estimate"

Alright, stick with me. This article is about marijuana dosage  and it provides good examples for how researchers go about quantifying their variables in order to properly study them. The article also highlights the importance of Subject Matter Experts in the process and how one research question can have many stakeholders. As the title states, the main question raised by this article is "How much weed is in a joint?". Why is this so important? Researchers in medicine, addictions, developmental psychology, criminal justice, etc. are trying to determine how much pot a person is probably smoking when most drug use surveys measure marijuana use by the joint. How to use in a statistics class: