Bella and I chose the topic “music” because we both listen to music often. This is a big part of both of our lives and we thought that this was the best topic that we can both relate too. We believe that more females, rather than males, will listen to pop music. Since this is what we think, we will explore that more with the data from the survey.
Response bias:
Question order bias – People are influenced by previous questions or are bored by the end of it. For example people might just put a random amount of hours that they listen to music because they just want to get the survey done. The way to avoid this is by mixing up the questions.
Social desirability bias – People may feel as though they have to answer what is socially acceptable. Such as saying that you listen to music for 2 hours a day instead of 5 hours because its socially acceptable. The way to avoid this is by not writing leading questions where it is obvious what the interviewer wants you to say.
‘Yes-Man’ phenomenon – People may feel inclined to give the interviewer the answer they want to hear. For example choosing Spotify over YouTube because its more “popular”. The way to avoid this in a survey leaving the responses as anonymous so that people feel more inclined to share.
Sampling bias:
Selection bias – Selection bias is when there is only one group that has been surveyed. You cant determine what is the most popular music streaming application from just year nines at All Saints College.
Non-response bias – When people complete the survey, some are not very enthusiastic about it so they will just fill in random answers that do not make sense. You cannot base your survey answers on these people as it will be invalid. For example, in this survey, one of the questions was how many hours do you listen to music in a day and some people said 40 hours.
| Platforms | Total Frequency | Girls | Boys |
| Spotify | 105 | 56 | 49 |
| Apple Music | 12 | 8 | 4 |
| YouTube Music | 10 | 1 | 9 |
| Soundcloud | 3 | 1 | 2 |
| CD/Vinyl | 5 | – | 5 |
| Not Sure | 3 | – | 3 |
This is our categorical frequency graph. This shows the frequency of the platform used from each gender. The mode of this graph is ‘Spotify’.
Number of hours Total frequency Girls Boys
| 0 | 7 | 2 | 5 |
| 0.15 | 1 | 1 | – |
| 0.25 | 2 | 1 | 1 |
| 0.5 | 2 | – | 2 |
| 0.75 | 1 | – | 1 |
| 1 | 29 | 11 | 18 |
| 1.5 | 3 | 2 | 1 |
| 2 | 26 | 13 | 13 |
| 2.5 | 1 | – | 1 |
| 3 | 15 | 9 | 6 |
| 3.5 | 3 | 1 | 2 |
| 4 | 14 | 8 | 6 |
| 5 | 7 | 4 | 3 |
| 6 | 8 | 3 | 5 |
| 7 | 3 | 3 | – |
| 8 | 2 | 2 | – |
| 9 | 3 | 1 | 2 |
| 10 | 3 | 1 | 2 |
| 12 | 1 | 1 | – |
| 14 | 2 | – | 2 |
| 15 | 2 | 1 | 1 |
| 30 | 1 | 1 | – |
| 40 | 1 | 1 | – |
| 48 | 1 | – | 1 |
This is our numerical frequency graph. This graph shows the frequency of the number of hours listened to music depending on someone’s gender.
Mean – 3.33
Median – 2
Mode – 1
Range – 15
Interquartile range – 3
Outliers – 30, 40, 48 hours
Our box and whisker diagram.
My Final Reflection:
Categorical:
The topic that we focused on was music, more specifically the platform in which different genders listen to music. The amount of people for boys and girls was quiet similar for all of these different platforms. However there was and outlier in the platforms used as Spotify has overcome all of the other applications by a lot.
Numerical:
The topic that we focused on was music, and in this data we focused the amount of hours different genders listen to music a day. The numbers of hours that these people listen to music are very similar between both genders. The only things that is different are some outliers in our data such as people listening to music for 30, 40 and 48 hours a day.
Reflection:
The conclusion that we have come to, based on our results, is that many people listen t music for large portions of their days. There is also an overwhelming majority of people that prefer Spotify over the other music applications. This means, within year nines at All Saints, that Spotify is better than the other platforms and it is more widely used.
