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Showing posts with the label distributions

Update: Using baby name popularity to illustrate unimodal and bimodal data

I love internet-based teaching ideas. They are free and current. At least they were current when I first posted them, but some of my posts are ten years old.  Such is the case for my old post about the Baby Name Voyage r and how to use it to illustrate unimodal, and bimodal distributions. Instead, please go to NameGrapher to show your students how flash-in-the-plan trendy baby names, like my own, have an unimodal distribution: As opposed to bimodal distributions, which flag a name as a more classical name that enjoyed a resurgence, like Emma: When I use this in class, I frame it between names that were trendy once and names that were trendy one hundred years ago and are again trendy. As a mom to grade-school-aged kids, I have certainly noticed this as a trend in kid names. So many Lilies and Noras!  I also make sure my students understand that this information is gathered via Social Security Administration applications from the federal government, to back up another clai...

Data distribution shapes via 1918 Flu Pandemic mortality distributions

I apologize in advance if you are pandemiced out. It is just that my brain won't stop seeing stats examples in information related to the COVID-19 pandemic. For instance, researchers are looking back at the 1918 Flu Pandemic in order to forecast how social distancing (or lack thereof) will affect mortality rates now. And these patterns, as illustrated by National Geographic, demonstrate different data distribution shapes . The data comes from a reputable source, is scaled to deaths per 100,000 as to allow for comparison, and the distributions are related to very important data. Other lessons your students can learn from this data: This is what good scicomm looks like. Also, sometimes a good data visualization is better than an accurate-yet-filled-with-jargon version of the same information. For instance, much has been shared about NYC vs St. Louis in terms of timing of quarantine. Here is the comparison yet again, but in an easier-to-follow description: There is a ton of...

Interactive NYC commuting data illustrates distribution of the sampling mean, median

Josh Katz and Kevin Quealy p ut together a cool interactive website to help users better understand their NYC commute . With the creation of this website, they also are helping statistics instructors illustrate a number of basic statistics lessons. To use the website, select two stations... The website returns a bee swarm plot, where each dot represents one day's commuting time over a 16-month sample.   So, handy for NYC commuters, but also statistics instructors. How to use in class: 1. Conceptual demonstration of the sampling distribution of the sample mean . To be clear, each dot doesn't represent the mean of a sample. However, I think this still does a good job of showing how much variability exists for commute time on a given day. The commute can vary wildly depending on the day when the sample was collected, but every data point is accurate.  2. Variability . Here, students can see the variability in commuting time. I think this example is e...

BBC's News' "Who is your Olympic Body Match?"

This interactive website from the BBC will match your student, using their height, gender, and weight, to their Rio Olympic body match. You enter your height, weight, age, and select your gender. It matches you with the athlete who is the most like you. It also provides good examples for distribution, and where you fall on the distribution, for Olympic athletes. I think it also gets students thinking about regression models. After you enter your data, the page returns information about where you fall on the distribution histogram for Olympic athletes by height, weight, and age for your gender. Then, the website returns your topic matches: How to use in class: 1) What other IVs could you collect to determine best sport match (DV)? Family income (I had access to soccer growing up, but not dressage horses)? Average temperature of hometown (My high school had a skiing club but not a beach volleyball club)? This gets your students thinking about multiple regression ...

Great Tweets about Statistics

I've shared these on my Twitter feed, and in a previous blog post dedicated to stats funnies. However,  I decided it would be useful to have a dedicated, occasionally updated blog post devoted to Twitter Statistics Comedy Gold. How to use in class? If your students get the joke, they get a stats concept. *Aside: I know I could have embedded these Tweets, but I decided to make my life easier by using screenshots. How NOT to write a response option.  Real life inter-rater reliability Scale Development Alright, technically not Twitter, but I am thrilled to make an exception for this clever, clever costume: This whole thread is awesome...https://twitter.com/EmpiricalDave/status/1067941351478710272 Randomness is tricky! And not random! ...