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Showing posts with the label Taylor Swift

Paired T-tests (Taylor's Version)

Ok, more Taylor Swift data for you. DID YOU KNOW that Spotify collects buckets and buckets of data about each and every song it provides (see:  https://www.spotify-song-stats.com/about ) So, I downloaded this information for 1989 and 1989 (Taylor's Version). So I could test for any differences between the recordings. Like, with data, not with my feelings and emotions. Specifically with a paired t -test. I get it. The sample sizes are very small. However, the data is still interesting. It makes sense that the tempo hasn't changed. Like, she did slow down or speed up anything. And that is super NS with an itty-bitty effect size. It is also interesting that acousticness has decreased. These are more heavily produced versions of the same songs (IMO), and while this change didn't achieve significance, it is a moderate effect size.  ANYWAY, you aren't really here for this information. You are here for data to share with your classes, yes? I'm here to help you teach your s...

The Taylor Swift Effect: Does Tay-tay's presence influence Travis Kelce's performance?

In what is a common occurance for this blog, it all started with a Tweet. A very punny Tweet https://twitter.com/ESPNFantasy/status/1716216331752624509 It begs the question: How are various indicators of Kelce's performance influenced by the presence or absence of one Taylor Swift? What she is steadily attending games this fall, we'll have to wait and see if her international tour, starting 11/7, changes that. Regardless, I'll update THIS SPREADSHEET over the season so you can run all of the independent t-tests you want with your students.  AND SOMEDAY I WILL UPDATE THIS SPREADSHEET TO INCLUDE WHETHER OR NOT THEIR CHILDREN ATTEND I SWEAR IT IS COMING.

The Unstoppable Pop of Taylor Swift: Data visualizations, variable operationalization, and DATA DATA DATA

  The unstoppable pop of Taylor Swift (reuters.com) Here are some ideas for using this to teach statistics: Data visualizations and visualization guides: With cats, y'all. And the Taylor Swift handwriting font. I love the whole vibe of this as well as how they explain their data visualizations. Operationalizing things: The page describes three Spotify metrics for music: Acousticness, danceability, and emotion. The data visualization contains a numeric value for each metric and a description of the metric's meaning. DATA!: Okay. This is an excellent example of things already. And it is delightful. Then I thought, "Oh, wouldn't it be fun if this was in spreadsheet form!" (I think that A LOT, friends). But, as I write a book and my syllabi, I don't have time for that,  BUT A REDDITOR DID HAVE TIME FOR THAT . Dr. Doon created a spreadsheet with 18 columns of Spotify data for each son. It doesn't include the Midnights data but is still a fantastic amount of dat...

A rank ordering of the Taylor Swift songbook.

File under: End of the semester stress blogging about a person who brings me joy. Taylor Swift (see: sampling error with Taylor ). Here is a new, VERY accessible example of ordinal data . Rob Sheffield, writing for Rolling Stone, rank-ordered ALL of Dr. Swift's songs.  https://www.rollingstone.com/music/music-lists/taylor-swift-songs-ranked-rob-sheffield-201800/bad-blood-2014-196114/ Also, introduce your students to Methods Section 😁. This rank order is based on the variable "Taylor genius". You could even use this as an example of anti-interrater reliability. This ranking comes from exactly one person. AND YOU'RE ON YOUR OWN KID DESERVED BETTER. Each ranking includes the best lyric from the song as well as a brief description of the Taylor Genius on display. Is this also an example of qualitative data? https://www.rollingstone.com/music/music-lists/taylor-swift-songs-ranked-rob-sheffield-201800/the-great-war-2022-1234617639/

Sampling Error (Taylor's Version)

Friends. You don't know what finding fun stats blog content has been like over the last few years. All of the data writers/websites I followed were always writing about, explaining, and visualizing COVID or political data (rightfully so). I prefer examples about puppies , lists of songs banned from wedding reception s, and ghosts . Memorable examples stick in my students' heads and don't presuppose any knowledge about psychological theory.  Due to the lack of silly data and my own life as a professor, mom of two, wife, and friend, my number of posts during The Rona definitely dipped.  But now, as the crocuses bloom in Erie, PA, the earth, and I, are finding new life and new examples. Nathaniel Rakich, writing for FiveThirtyEight, wrote a whole piece  USING TAYLOR SWIFT TO EXPLAIN POLLING/SAMPLING ERROR S. Specifically, this article tackles three different polling firms and how they went about asking Americans which Taylor Swift album is their favorite Taylor Swift album....