Introduction
Mobile phones have been improving countless times from first invention until today. In the early years of development of mobile phones, the cost for regular consumers to obtain a mobile phone was extremely high. For example, the first mobile phone, Motorola DynaTAC 800x, launched in 1983 was sold at a price of around $4000. It was obvious that no average Joe can afford to buy a mobile phone at that time. When compared to the price of mobile phones these days, the difference is astounding.
Mobile phones provide easy and simple ways to communicate with families and friends at all times and it can be used in any place. It is very convenient to use mobile phones because of the small weight and size.
Background of Study
The great advantages of mobile phone will make sure students’ life become more efficient and easier. Because of universities learning program these days strongly depend on using of mobile phone, every student is encouraged to buy their own mobile phone. This project is to study whether students’ income will affect the students’ mobile phone expenses among School of Computing UTM students.
Objectives
- To study universities students’ expenses in buying mobile phone.
- To study the relationship between students’ income and students’ mobile phone expenses.
- To know students mobile phone brand preference.
- To study student’s behaviour patterns in buying their own mobile phone.
- To know how much student is willing to spend for buying mobile data.
PDF of our report
Video
The video for our presentation has been uploaded in e-learning by Isyraff.
Thank you :)
Conclusion
To conclude, we have recorded 60 students’ response as a sample of data with 31 male respondents and 29 female respondents. The majority of respondents are 1st year students with 44 respondents and followed by 11 respondents from 2nd year students and only 5 students from 4th year students.
The most preferred smartphone brand is Apple with 13 students (21.7%) while the least preferred smartphone brands are Google and Redmi with only 1 student each (1.7%)
The highest frequency of monthly income of students each month is RM500 and below with 36 students (60%) and the lowest frequency is range RM1500-RM2000 and RM2500-RM3000 with frequency of 3 students (5%) each range.
Last but not least, the relationship between students’ monthly income and monthly spending for data plans has weak negative relationship and non-linear. From this, we can know that when the students’ monthly income decrease, monthly spending for data plans by students is increasing.
Reflection
Upon completion of this project, I have gained a lot of knowledge and understanding about gaining information and interpreting it empirically. To be more precise, this project has taught me the most popular mobile phone brand among students, their average income, students' expenses on mobile phones and how all of those input from the respondents correlate between one another.
While completing the project, I can see that there is a wide usage of statistical terminologies in identifying numerical data. For example, the representation of our data using charts and graphs in our project gave us a clear view on the information that we have collected. This is done in order for to come to a conclusion or make an inference based on the graphs/charts. Plus, the descriptive statistics such as calculating the mean, mode, median, variance and standard deviation are important keys for us to extract more complex information from the sample data.
In conclusion, I have gathered that statistical analysis is a powerful tool to ensure the sustainability of data to be collected and presented in a systematic way.