I often share news stories that illustrate easy-to-follow, engaging research that appeals to undergraduates. For the first time, I'm also providing a mini data set that 1) mimics the original findings and 2) provides an example of ANOVA.
This story by Patty Neighmond, reporting for NPR, describes a study investigating the role of music in pain reduction. The study used three groups of kids, all recovering from surgery. The kids either 1) listened to music, 2) listened to an audio books, or 3) sat with noise-cancelling ear phones for 30 minutes. The researchers found that kids in both the music and audio book experienced pain reduction levels comparable to over-the-counter pain medication while the control group enjoyed no such benefits.
And the research used the 10-point FACES scale, allowing for a side discussion about how we collect data from humans who don't have the best vocabularies or limited communication skills.
Here is a data set generated via Richard Landers' data set generator and modified as to use a 1-10 FACES scale used in the original research (yes, the n-size is small for this design). It approximates the original findings: Statistically significant ANOVA, with post-hocs that demonstrate that Audio Book and Music conditions do not differ significantly but that participants in theses two groups report significantly less pain that the control condition.
This story by Patty Neighmond, reporting for NPR, describes a study investigating the role of music in pain reduction. The study used three groups of kids, all recovering from surgery. The kids either 1) listened to music, 2) listened to an audio books, or 3) sat with noise-cancelling ear phones for 30 minutes. The researchers found that kids in both the music and audio book experienced pain reduction levels comparable to over-the-counter pain medication while the control group enjoyed no such benefits.
And the research used the 10-point FACES scale, allowing for a side discussion about how we collect data from humans who don't have the best vocabularies or limited communication skills.
This study can also be used as a way to explain ANOVA. The researchers didn't use ANOVA (and the data I provide below IS NOT the original data), but the original design and findings do provide us with three levels of a factor as well as some significant post-hocs.
Here is a data set generated via Richard Landers' data set generator and modified as to use a 1-10 FACES scale used in the original research (yes, the n-size is small for this design). It approximates the original findings: Statistically significant ANOVA, with post-hocs that demonstrate that Audio Book and Music conditions do not differ significantly but that participants in theses two groups report significantly less pain that the control condition.
Audio Book |
Music | Control |
| 5 | 5 | 4 |
| 6 | 4 | 8 |
| 7 | 4 | 7 |
| 2 | 7 | 6 |
| 6 | 6 | 10 |
| 3 | 4 | 6 |
| 4 | 6 | 10 |
| 8 | 4 | 8 |
| 5 | 3 | 5 |
| 4 | 5 | 6 |
Now, if you have the students listen to the news story first, they are going to know the results. I don't think this is a bad thing, necessarily. I think this could be used when first introducing students to ANOVA as an example with training wheels (interesting news story to listen to for four minutes followed by a statistical exercise for which they know the outcomes). Additionally, I teach statistics to a lot of non-psychology majors (nursing, pre-physical therapy, pre-physician assistant) so a medical example helps me reach those students.
This could also be used as a prompt a discussion about turning this study into a more complicated one-way ANOVA (include more levels of your factor, like 30 minutes of video games or TV) as well as how you could turn the original study into a factorial ANOVA (by including severity of surgery, length of hospital stay, age of child, etc.).
This could also be used as a prompt a discussion about turning this study into a more complicated one-way ANOVA (include more levels of your factor, like 30 minutes of video games or TV) as well as how you could turn the original study into a factorial ANOVA (by including severity of surgery, length of hospital stay, age of child, etc.).
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