Situation

Students increasingly listen to music while studying, but there’s little concern on whether it actually helps. I surveyed 50 students across academic levels about their music habits, productivity, and focus.


Task

-> Clean the data set
-> Make plot/ table to answer 5 questions:
1. How often people listen to music (across age/ study level).
2. What’s the Productivity Score by Music-listener and the non-listener.
3. What type of music help productivity the most.
4. What type of work that listening to music would help/ distract.
5. How they think music would help them (the opinion column) compare to if music actually help them (calculated by distracting and and productivity point).

-> The goal was to understand: does music actually improve studying, and does it matter what type you listen to or what task you’re doing?


Analysis

How often people listen to music (across age/ study level)

Proportional bar charts examining music listening habit across age and academic level

## # A tibble: 8 × 4
## # Groups:   age [4]
##   age      listens     n propo_a
##   <fct>    <chr>   <int>   <dbl>
## 1 Under 18 No          1   0.1  
## 2 Under 18 Yes         9   0.9  
## 3 18–20    No          4   0.167
## 4 18–20    Yes        20   0.833
## 5 21–23    No          2   0.25 
## 6 21–23    Yes         6   0.75 
## 7 24+      No          4   0.5  
## 8 24+      Yes         4   0.5

## # A tibble: 7 × 4
## # Groups:   level [5]
##   level         listens     n propo_le
##   <fct>         <chr>   <int>    <dbl>
## 1 Middle school No          1    1    
## 2 High school   Yes        11    1    
## 3 Undergraduate No          9    0.273
## 4 Undergraduate Yes        24    0.727
## 5 Graduate      No          1    0.25 
## 6 Graduate      Yes         3    0.75 
## 7 Doctorate     Yes         1    1

Music Listening Habit Among Undergraduates (by Age)

Proportional bar charts examining the music listening habit among undergraduate by Age

## # A tibble: 7 × 6
##   age      listens     n   pct n_total age_label        
##   <fct>    <chr>   <int> <dbl>   <int> <fct>            
## 1 Under 18 Yes         1 1           1 "Under 18\n(n=1)"
## 2 18–20    No          4 0.190      21 "18–20\n(n=21)"  
## 3 18–20    Yes        17 0.810      21 "18–20\n(n=21)"  
## 4 21–23    No          2 0.286       7 "21–23\n(n=7)"   
## 5 21–23    Yes         5 0.714       7 "21–23\n(n=7)"   
## 6 24+      No          3 0.75        4 "24+\n(n=4)"     
## 7 24+      Yes         1 0.25        4 "24+\n(n=4)"

Productivity Score by Music Habit Among Undergraduates (by Age)

Boxplots comparing productivity scores between listeners vs non-listeners among the undergraduates by Age

Comment

18–20 (most reliable, n=21): both groups are very similar. Non-listeners have a slightly wider spread (4–8) while listeners cluster between 5–7. No strong difference here.
Among undergraduates, music listeners tend to report equal or higher productivity than non-listeners, with the pattern being most visible in the 21–23 age group.


What type of music help productivity the most

Bar chart ranking music types by average productivity score

## # A tibble: 6 × 3
##   music_type   avg_productivity     n
##   <chr>                   <dbl> <int>
## 1 EDM                      5.07    15
## 2 Hip-hop/Rap              5.94    18
## 3 Instrumental             6.18    40
## 4 Jazz                     5.82    17
## 5 Other                    6.16    19
## 6 Pop                      6       32

What type of work that listening to music would help/ distract

Dodged bar chart mapping which tasks music helps vs distracts

## # A tibble: 5 × 2
##   type            n_helps
##   <chr>             <int>
## 1 Creative work        37
## 2 Memorization          5
## 3 Problem-solving      22
## 4 Reading              16
## 5 Writing              21
## # A tibble: 5 × 2
##   type            n_distracts
##   <chr>                 <int>
## 1 Creative work             8
## 2 Memorization             40
## 3 Problem-solving          18
## 4 Reading                  31
## 5 Writing                  24

How they think music would help them (the opinion column) compare to if music actually help them (calculated by distracting and and productivity point)

Stacked bar chart comparing perceived vs actual benefit using a productivity/distraction threshold

Perceived opinion vs actual help (threshold-based)
High productivity = productivity >= 7
Low distraction = distraction <= 5

## # A tibble: 6 × 6
##   opinion actually_helped            n   pct n_total op_label       
##   <ord>   <chr>                  <int> <dbl>   <int> <fct>          
## 1 No      Actually Helped            3 0.75        4 "No\n(n=4)"    
## 2 No      Did Not Meet Threshold     1 0.25        4 "No\n(n=4)"    
## 3 Maybe   Actually Helped            4 0.167      24 "Maybe\n(n=24)"
## 4 Maybe   Did Not Meet Threshold    20 0.833      24 "Maybe\n(n=24)"
## 5 Yes     Actually Helped            7 0.318      22 "Yes\n(n=22)"  
## 6 Yes     Did Not Meet Threshold    15 0.682      22 "Yes\n(n=22)"

Comment “No” group (n=4): 75% actually met the threshold. So people who think music doesn’t help them are ironically performing well by the metric. But n=4 is far too small to mean anything.

“Maybe” group (n=24): only ~17% met the threshold. The largest group is the most uncertain, and most of them didn’t meet the productivity/distraction threshold.

“Yes” group (n=22): about 32% met the threshold. People who believe music helps them are not necessarily performing better by the objective measure.

The ‘No’ group (n=4) is too small to draw conclusions from, but the ‘Yes’ vs ‘Maybe’ contrast is still meaningful

Result

  1. Music listeners and non-listeners report nearly equal productivity
  2. Instrumental music scores highest for productivity among all music types
  3. Music helps most with creative tasks but is the worst choice for memorization which suggest the cognitive demand of the task matters more than whether you listen or not
  4. Most interestingly, students who said “Yes, music helps me” only met the productivity threshold 32% of the time, suggesting an illusion of productivity — where music’s mood-boosting effect is mistaken for actual cognitive output