Week 9: Success!

Aashi H -

Welcome back, everyone! We hit 30 responses this week! This was the targeted response amount for my survey to successfully apply the Match Paired t-test. This week, I have been working on transferring my data into visual graphs and diagrams to put into my presentations. I will display a few here, as well as discuss a few trends I have been seeing in the data.

Genres of Music Chosen

Over the course of a month, we had a little over 30 responses. About 75% were crew members, 22% were Shift leaders, and 3% were Managers.

The above graph is a distribution of the how many participants chose what music genre. Pop, rap, and rock were the most popular genres. Only one participant chose classical and zen/spa; Jazz and country were not chosen at all.

Average Change in Scores

In order to see if a music genre impacted the change in the PSS-10 score, the following graph shows the average decrease in the PSS-10 score per genre.

This graph was made with error bars with a 10% margin of error. Because the error bars overlap for the pop, rock, and zen/spa genres, there is no statistically significant difference that proves one genre had an impact on the decrease of PSS-10 scores over the other. The error bars for zen/spa and classical overlap, suggesting that there may not be a significant difference between classical and zen/spa, but there may be between classical compared to the pop and rock genres. One likely reason for this is the number of responders for the zen/spa and classical genres. Because there is only one data point for both of these genres, a larger sample size is required to draw further conclusions. Lastly, the rap error bar does not overlap with any other genre. This suggests that rap music does cause the lowest decrease in the PSS-10 scores. A likely reason for this could be that rap music is known to be more aggressive than the other genres, so it may not have the same calming effect on the brain as the other genres. Once again, a larger sample size is required to generalize this conclusion.

Side-by-side Bar Graphs

In order to understand the following graphs, it is important to first understand how the PSS-10 test is scored. There are ten questions on the test. Participants choose their answer on a scale of 0-4:

0 – never | 1 – almost never | 2 – sometimes | 3 – fairly often | 4 – very often

The questionnaire is scored by adding up all the numbers a participant chose for each question. However, for four of the ten questions, the answers are reversed. This is to prevent participants from identifying a pattern of responses they can use on the questionnaire. For those four questions, the scoring is reversed:

0 = 4 | 1 = 3 | 2 = 2 | 3 = 1 | 4 = 0

Normal Scoring Bar Graph

Below is an example of a bar graph for a question that is scored normally. The trend line is expected to move towards the left. This is because before listening to music, the hope is that the participant will answer on the higher side; after listening to music, the participant will hopefully feel less stressed, meaning they score lower. Therefore, the trend line is expected to move to the left for these normal scoring graphs.

In the graph above, we can see that this expectation was followed.  For the pre-test, participants tended to report feeling upset because of something that happened unexpectedly. However, after listening to the music, the trend shifted, and participants reported feeling less stressed. We can see this through the scores of 0 and 4, where participants reported feeling very stressed before and never stressed after. Additionally, we can see this trend in the more centered post-test responses around the 1 and 2 scores, suggesting that music did have an impact on the perceived stress levels of participants.

Reversed Scoring Bar Graph

Below is an example of a bar graph for a question that is scored reversed. The trend line is expected to move towards the right. This is because before listening to music, the hope is that the participant will answer on the lower side due to the way the question is worded; after listening to music, the participant will hopefully feel less stressed, meaning they score higher for these particular questions. Therefore, the trend line is expected to move to the right for these normal scoring graphs. Let’s look at an example.

In the graph above,  we can see that this trend is followed as expected. The pre-test scores are more centered to the left side of the graph in the 1-2 score range, and the post-test scores are centered to the right, with a majority of scores being a 3. This shows that participants felt that they could control irritations around them more likely in the post-test, rather than feeling unable to control irritations in the pre-test.

Now, not all graphs show a trend like this. Some of the graphs’ trend lines are exponential rather than polynomial, and require further analysis. One theory I had when going through all the data is that music may make participants feel more positive about their environments. Along with making participants feel calmer and centered, listening to their preferred genre of music may improve participants’ mindsets, contributing to the successful trends I am seeing.

Thank you for reading! Over the next two weeks, I am working on my presentation and paper, compiling all the work we have done so far this year into a way that makes it easy to understand. I hope to see you at my presentation in the auditorium on Friday, April 25th, at 9 am. Once again, a big, big thank you to all my mentors in the process so far! This project would not be a success without your guidance.

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Comments:

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    allison_y
    Wow, I love the attention to detail and the organized visuals Aashi! It seems like many things followed your expectations (as seen in the last two graphs). Was there anything in particular that was drastically unexpected in your data?
    Shreyash Prakash
    This is such an impressive update Aashi—congrats on hitting your response goal! It’s clear how much effort and thought you’ve put into not just collecting the data but interpreting it critically. I love how you’re using error bars and reversed scoring to deepen your analysis—it shows a really strong understanding of experimental design and psychological metrics. The insights about rap and stress reduction are especially interesting, and you do a great job explaining the nuances around sample size limitations. Can’t wait to see your final presentation on the 25th—it sounds like it’s going to be both polished and meaningful!
    aashi_h
    Hey Allison, thank you for the question! I was surprised by some of the graph trends I saw. As I mentioned, not all graph trends were as straightforward as the ones above. This makes me think that maybe the PSS-10 needs some more testing before being fully applied in the clinical field. It may also suggest that certain questions have a higher weight than others in the survey. Just an interesting observation I wasn't expecting to see.
    aashi_h
    Thank you for the kind words, Shreyash!
    tanay_n
    Hey Aashi! Your results are fascinating! Coming into the final week of your project, what has been the most exciting part?
    aashi_h
    Thank you for the question, Tanay! I think the most exciting part of this journey is seeing how all my work is coming together. There have been so many moving pieces throughout the project, and so many hurdles to hop through to make it possible. I'm so happy to finally be able to share my results with everyone!

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