Mobile Phone Choice and Factors Influencing It: A Study on La Trobe University Students

This report analyzes the mobile phone choice of La Trobe University students and its relation with factors such as gender, earnings, and discounts available. The study uses random sampling and a sample size of 175 to draw conclusions.

Cover Page
BUS1BAN Major Assignment
Teacher’s Name Najam Iqbal
Workshop Details
(Time, day, room)
DW 212 EBL 5, Wednesday’s 2PM till 4PM
Students ID
Number
Students Name Student contribution*
(%)
e.g. 50% means the
student will receive 50%
of the marks awarded
Students Signature
S19416453 Candace Hughes
19095339 Nathan Sleep
18856078 Guyang Zhang

Introduction
The objective of this report is to highlight the mobile phone choice exhibited by students at the
La Trobe University and the relation of this choice with different factors such as gender, earnings
and underlying discount available. The data used for this research has been derived using random
sampling from the population data comprising of the survey results of the various students
studying at La Trobe University. The sample size selected for this study is 175 and considering
the sample size and random sampling, it is expected that the sample obtained would be
representative of the underlying population of interest.
Data Analysis
Section A: Basic Analysis
1. The numerical summary and graphical representation of gender proportions.
Numerical summary: Pivot table
Graphical representation: Pie chart
1

2. Average monthly bills of students based on gender distribution is shown below:
Graphical representation: Column chart
3. Average monthly earning of students based on gender distribution is shown below:
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Graphical representation: Column chart
In order to find the relationship between monthly earning and money spent on mobile usage.
3

Considering the dismal value of coefficient of determination, it may be concluded that the
relationship between earnings and money spent is not related for either of the genders (Hillier,
2016).
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(4) The numerical summary to represent the market share of each mobile brand by gender is
shown below:
Relative frequency table
Section B
(5) The average earning of students and their mobile phone choices are represented in the form
of pivot table shown below:
5

From the above, it seems that the earnings and mobile choice is related considering the deviation
in average earnings of the respective phone users. For instance, average earnings of LG mobile
users are almost half that of Apple mobile users which is quite significant and cannot be ignored.
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It is apparent that there seems to be difference in the mobile choice in the different earning
groups. For high income earners, it is apparent that only Apple and Samsung are the two choices
which are considered as premium brands. LG is only concentrated with the low income group.
Hence, it is evident that choice of mobile phone does seem to be different amongst the different
earning groups.
(6) The requisite results obtained are highlighted below.
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8

Considering the above results and also the high coefficient of determination, it is apparent that as
the discount on Samsung Galaxy phone tends to increase more proportion of users would tend to
make a switch towards Samsung from iPhone (Flick, 2015).
(7) The requisite output is shown below.
9

It is apparent that males seem to be more receptive to the discount in comparison to females.
This is apparent from the higher slope coefficient of males in comparison with females. This
highlights that there is a difference in the gender with regards to response to the discount (Hair
et. al., 2015).
Section C
(8) The requisite computation is shown below.
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95% confidence interval
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With 95% confidence, we can state that population proportion of selected individual being male
would lie between 0.453 and 0.528. Also, with 95% confidence, we can state that population
proportion of selected individual being male would lie between 0.476 and 0.552 (Eriksson and
Kovalainen, 2015).
(b) Number of students who will use mobile phones is shown below:
Sample proportion (students are using smart phone) = 678/679 = 0.9985
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From the above output, we can conclude with 95% confidence that the population proportion
using a mobile phone would lie between 0.9947 and 1.0000 (Flick, 2015).
(9) The requisite computation is shown below.
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With a 95% confidence, it can be stated that average earnings of the male population would lie
between $ 1,126.21 and $1,334.84. Further, with 95% confidence, it can be states that average
earnings of the female population would lie between $ 1,152.41 and $ 1.369.41 (Hillier, 2016).
(10) Hypothesis testing
Step1
Hypotheses
H0 : p ≤ 0.40
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Ha : p >0.40
Step 2
Test statistics
Proportion of iPhone users = 138/175 = 0.7886
Now,
Standard deviation = √ 0.7886 ( 1−0.7886 )
175 =0.03086
The z value z= 0.4−0.7886
0.03086 =−12.5889
Step 3
The p value corresponding to z value comes out to be 0.00.
Step 4
Level of significance = 1%, 5%, 10%
Step 5
It can be seen from the above that p value is lower than all the levels of significance and
therefore, sufficient evidence is present to reject the null hypothesis and to accept the alternative
hypothesis (Hair et. al., 2015). Therefore, the claim that market share of iPhone is higher than
40% is correct.
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Summary and Discussion
On the basis of the above analysis, it may be concluded that the choice of mobile phone is
significantly influenced by the earnings as high income earners do not use any phone except
Samsung Galaxy and Apple iPhone. Also, there is significant different between the gender based
trend related to spending on money and also the earnings level. However, no significant
relationship has been found between earnings and money spent for either of the genders. Further,
it is also seen that as a higher discount is given by Samsung Galaxy, a larger proportion of
students tend to make a shift from Apple iPhone. This trend is more prevalent amongst the
males. Further, it has also been found that iPhone share is more than 40% for La Trobe
university students as well.
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References
Eriksson, P. and Kovalainen, A. (2015) Quantitative methods in business research 3rd ed.
London: Sage Publications.
Flick, U. (2015) Introducing research methodology: A beginner's guide to doing a research
project. 4th ed. New York: Sage Publications.
Hair, J. F., Wolfinbarger, M., Money, A. H., Samouel, P., and Page, M. J. (2015) Essentials of
business research methods. 2nd ed. New York: Routledge.
Hillier, F. (2016) Introduction to Operations Research 6th ed. New York: McGraw Hill
Publications.
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