Eco-Fone Report Assignment 2022

Running head: ECO-FONE REPORT
ECO-FONE REPORT
Name of the Student
Name of the University
Author Note

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Introduction:
The assignment basically deals with analysing the market of smartphones in terms of
research of Deloitte paper for a particular company named Eco-Fone that is new in the
market and wants to expand their business in the country. The overview of current market
growth of smartphones for different ages are estimated by statistical methods and analysing
the growth it recommendation is provided for Eco-Fone whether to go for market expansion
(Deloitte 2020). The features of smartphones that makes them attractive are also discussed in
brief in correspondence to market expansion pros and cons table. Statistical tests are also
performed here to compare sales of different stores of Eco-Fone and thus to find if sales of
smartphones depends on location advantages.
Task 1:
The number of people in the labour force of UK is approximately 33.5 million and currently
there are 33 million people are working in the country which makes about 95% of the labour
force as per the Deloitte research. The research also found that all the people inside the
sample of survey use smartphone for at least one activity that is related to the business and
the sample consist of only 50% of the people who responded to the survey. Also, it is found
the by statistical research as by Deloitte that just over 50% of the people use smartphones for
business or work related activities. In the common way the smartphone usage can be divided
into three primary categories that are about 44% for emails, 23% for calendar management
and 34% in voice calls. The modern smartphones are very easy to use for doing emails,
setting remainders via calendar apps and HD quality voice calling, thus, it is very much
expected that people will use the smartphones for these activities. Some activities in the
smartphone are still complex and known specific knowledgeable persons like reporting
system and extracting legacy information and thus these activities are rarely used as found the

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sample (Rozgonjuk and Elhai 2018). The vastly used activities by the Deloitte report are
mainly mobile browsing, photo editing and instant messaging which are provided by a
number of apps in smartphone. The most popular application as found in the sample is
WhatsApp and this is used by approximately 43% of workers in sample for at least once in a
day. There are also several moderate level application usage that are specially used for the
work flow activities. These activities include time sheet submission, expenses sheet
submission and connecting to intranet by browser which are used typically by four percent,
five percent and six percent of the workers in the sample. The mobile usages in the year 2016
and 2017 are shown in the following mixed bar chart (Wun et al. 2016).
Email
Making standard calls
Calendar management
Viewing documents
Time/workload management
Internet usage for making voice calls (VoIP)
Company Intranet access
Tethering from phone to laptop
Document or spreadsheets editing
Accessing company files for netwroks/ storage
Logging in the working hours
Expenses submission
Other
None of these
0 10 20 30 40 50 60
Usage of Smartphone for various activities in 2016 and
2017
Proportion in %(in year 2017) Proportion in %(in year 2016)
Task 2:
Now, the percentage information of the smartphone usage from the year 2012 to 2017 is
obtained from the Deloitte report and this is displayed in the following line chart. The

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forecasting equation that fits the percentage usage of smartphone is found to by the regression
polynomial of 2nd order which explains the variation of % smartphone usage in terms of
variation of year is about 99.95% which can be considered a very good model for predicting
percentage smartphone usage by year (Tanwani and Memon 2016). The linear regression
model is not a good fit to the data as the it has very less explanation of percentage usage of
smartphone in terms of year compared to the polynomial regression equation as obtained
from the R^2 or coefficient of determination value. The line chart also depicts that the graph
is a curve instead of a straight line (Albright and Fox 2019).
2012 2013 2014 2015 2016 2017
0
10
20
30
40
50
60
70
80
90
52
62
70
76 81 85
f(x) = − 0.75 x² + 11.7642857142857 x + 41.2
R² = 0.999513836948392
Smartphone usage line chart
Year
% of Smartphone usage
Thus from the polynomial regression model the predicted percentage usage of smartphones in
2018 is -0.75*(7^2) + 11.764*7 + 41.2 = 86.798% and the predicted % usage of smartphones
in 2019 will be -0.75*(8^2) + 11.764*8 + 41.2 = 87.312%.
Task 3:
The Smartphones are very popular to the older people because of their plenty of features as
found in research by BBC news article. As found by research that in the age group of 55 to 75
years almost 75% of people use smartphones for entertainment and personal usage. The

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wealth of the older age group is expected to be more than the younger age group as they have
done much savings in their lifetime than the younger ones and hence older people can buy
expensive smartphone much easily than the younger ones. However, enough money is not the
only cause for buying new smartphones by the older people, the real cause to buy
smartphones is the attractive features of the phones. The different features of the smartphones
are ordering cabs in a busy city through apps, high definition sound quality and wide screen
display of sounds that are very convenient for older people due to their poor eyesight and
hearing ability. Other useful features of smartphones include parking meters payments
through apps, ordering online food from different food delivery apps, paying electricity and
telephones and other bills online that are very easy and saves a lot of time for the older
persons (BBC News. 2020). The operating system installed in smartphones are very easy to
use like the latest Android version or IOS and thus older people can easily grasp the modern
technology. Some Smartphones also includes fingerprint unlocking and facial recognition
unlocking which are pretty amazing to use and particularly suitable for the older people as
they don’t like typing passwords or unlocking by pattern most of the times.
Task 4:
Should we expand our business to Kingston?
Pros Score/10 Cons Score/10
The number of brands
dominating the market is very
few which are Apple and
Samsung. Hence, there is very
6
Samsung and Apple holds very
large market, 48% and 35%
respectively.
4

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The number of consumers of
smartphones are indicated to
increase in future
7
The buyers of new smartphones
tends to buy from recognized
brands like Samsung and apple.
5
In each year the monthly
subscribers network providers is
increased.
8
Pay-as-you-go trend increasing
each year and not much profit is
generated in each year by the
trend.
5
New technologies are grasped by
many of the old people as offered
6
Some new techs are complex to
adapt and thus it reduces the
popularity of smartphones.
4
Total Pros 27 Total Cons 18
Average Pros 6.75 Average Cons 4.5
Hence, as found from the sum and average scores of total pros and cons score table the sum
and average of pros is way higher than the same of cons. Hence, expansion of business in
Kingston will be much beneficial for Eco-Fone.
Task 5:
a)
Given, mortgage schedule = 15 years
Initial amount or mortgage initial value = £350,000
Rate of mortgage = 7%

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The monthly payments to pay-off the mortgage is calculated by using the PMT function in
excel as given below (Brickner and Mahoney 2018).
Loan Amount £
3,50,000.00
Interest rate 7%
Years 15
Monthly
Payments
£
3,145.90
Hence, monthly cost is £ 3,145.90.
b) The top eight commercial lenders and their logos are given in the following table.
Lender name Logo
NatWest

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RBS
HSBC
Barclays
Lloyds bank

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TSB
Bank of Scotland
Clydesdale Bank
Task 6:
Given, sample size of first shop n1 = 40
Sample mean for first shop = £100

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Sample standard deviation of first shop = £20
Sample size of first shop n2 = 40
Sample mean for second shop = £90
Sample standard deviation of second shop = £40
Now, in this problem it is required to be found that if the population means of the two shops
are significantly different or same to each other.
Now, in this case the t test will be used to as the population standard deviation is unknown
and it is assumed that the populations are approximately normally distributed. It is also
assumed that population variances of daily takings are the same for simplicity of calculation
and the significance level for the test is 5% (Delacre, Lakens and Leys 2017).
Null hypothesis (H0): The population means of net daily takings from two shops are equal
(μ1 = μ2)
Alternative hypothesis (H1): The population means of net daily takings from two shops are
not equal (μ1 ≠ μ2).
T-test table:
T Test
sample mean shop
1(m1)
100
sample mean shop
2(m2)
90
sample sd shop 1(s1) 20
sample sd shop 2(s2) 40

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sample size shop
1(n1)
40
sample size shop
2(n2)
40
hypthesized mean
difference
0
Assuming equal
variance
pooled variance(sp) 1000 ((n1-1)*s1^2 + (n2-1)*s2^2)/(n1+n2-2)
t score 0.044721 (m1-m2)/(sp*(1/n1 + 1/n2))
df 78 n1+n2-2
Two tailed t test
p value 0.964444
Significance level 0.05
Decision Not enough proof to reject the null hypothesis as p value more
than significance level
Thus the results from the t test table shows that not enough evidence to reject the null
hypothesis or can be concluded that population means of the daily takings of the two shops
are equal (Derrick et al. 2018).
Task 7:
Now, as there is chance that respondent may give excessive low or high ratings to the
questions asked to them due to biasness hence average is not a good measure to judge the

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overall response of the questions as average is vulnerable to the outliers. Hence, responses of
the six questions that are asked are measured using median or the median value of the
response is considered for evaluation of the overall summary (Yadav, Singh and Gupta
2019). The responses are given from highest to lowest for best to worst response in a
chronological manner.
IDS Q1 Q2 Q3a Q3b Q3c Q3d Q4 Q5 Q6
Media
n
3 3 2 2 4 3 2 2 4
Hence, the summary of responses can be evaluated as given below.
Median of the customers bought product or service in between 3 to 6 month. There is
evidence that median customers used products or service of eco-Fone for 1 to 3 years.
Median customers have a view that the quality of services or support is fair. Median
customers think that product quality of Eco-Fone is fair and the sales staff quality of Eco-
Fone is excellent. Also, by median customers the price or value of product or service of Eco-
Fone on an average is good. Overall the products or services of Eco-Fone are dissatisfied to
the customers. The median customers are unlikely to do business with Eco-Fone and median
customers are likely to recommend Eco-Fone brand to others.
Task 8:
Given,
Total invoices sent by eco-Fone = 10000.
Average number of returned invoices in a month (λ) = 2.
Suppose X is the expected number of returned invoices in a month.

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Now, as the sample size 10000 is very large, thus Poisson distribution can be approximated y
binomial distribution.
Poisson distribution probability mass function
P(X=x) = e−λ∗λx
x !
Thus probability of returning more than three invoices in month by Poisson distribution is
P(X>3) = 1- (P(X=0) + P(X=1) + P(X=2) + P(X=3)) =
1 – ( e−2∗20
0 ! + e−2∗21
1! + e−2∗22
2 ! + e−2∗23
3 ! ) = 0.1428 = 14.28%.
As the probability of more than three return or error of invoices is very less than 50% hence
the quality of invoices sent by Eco-Fone is very good and it meets requirement of Eco-Fone.
Task 9:
All references are given towards the end of all task.
Task 10:
Now, in this task the business overview of Eco-Fone is presented in a very short paragraph.
The Smartphones market is expanding as per the report of Deloitte and data analysis
performed in the first as not only the young generation but also the old people are buying
smartphones due to their attractive features and simplicity of usage. The market is still
somehow competitive for Eco-Fone as most of the customers are going with the brand name
and the recognized two brands that are currently having most of the market share are
Samsung and Apple. Thus expansion of business in the whole United Kingdom is still a
beneficial choice for Eco-Fone despite of uneven competition. This is because of the
somehow exponential usage increase of smartphones over the years as indicated from the
non-linear trend line as found using curve fitting method in excel. The sum and average of

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pros scores for expanding business to Kingston for Eco-Fone is more than the sum and
average of cons score and hence Eco-Fone should further go for expanding their market in
stores all over the country. If a mortgage is needed for eco-Fone for business expansion then
it can be provided by any reputed bank as listed in 5b and the calculation of EMI payable for
a handsome amount loan with moderate interest rate of 5% is also calculated in the earlier
task. Further sample research of two store net daily takings data shows that the average net
daily taking are not significantly different from each other indicating that Eco-Fone can
expand business almost anywhere in popular cities and sales of smartphone are not location
biased. The quality of invoices sent by Eco-Fone are also satisfactory as the probability of
more than three error invoices in a month is very less than 50%.
Conclusion:
Thus it can be stated that the business overview of Eco-Fone is overall good and there is
sufficient advantage if Eco-Fone goes for expanding the market of smartphones in United
Kingdom. Eco-Fone must also spent enough time for research and development for
understanding customer needs more accurately to release more advanced versions of
smartphones in the market. This will also help the company to gain quick recognition in
market and always keep them in competition to the big brands like Apple and Samsung.

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References:
Albright, B. and Fox, W.P., 2019. Mathematical modeling with excel. CRC Press.
BBC News. 2020. Smartphone Sales Boom With Over-55S. [online] Available at:
<https://www.bbc.co.uk/news/technology-41319684> [Accessed 15 April 2020].
Brickner, D.R. and Mahoney, L.S., 2018. Factoring in the Time Value of Money with Excel:
This Technology Workshop Shows How to Use a Plethora of Excel Functions to Perform the
Calculations Needed for This Analysis. Journal of Accountancy, 225(3), p.34.
Delacre, M., Lakens, D. and Leys, C., 2017. Why psychologists should by default use
Welch’s t-test instead of Student’s t-test. International Review of Social Psychology, 30(1).
Deloitte.co.uk. 2020. [online] Available at:
<https://www.deloitte.co.uk/mobileuk2017/assets/img/download/global-mobile-consumer-
survey-2017_uk-cut.pdf> [Accessed 15 April 2020].
Derrick, B., Ruck, A., Toher, D. and White, P., 2018. Tests for equality of variances between
two samples which contain both paired observations and independent observations. Journal
of Applied Quantitative Methods, 13(2).
Rozgonjuk, D. and Elhai, J., 2018. Problematic smartphone usage, emotion regulation, and
social and non-social smartphone use. In Proceedings of the Technology, Mind, and
Society (pp. 1-1).
Tanwani, S. and Memon, B.A., 2016. Trend Line Analysis of Weight versus Compressive
Strength of Concrete. International Journal of Emerging Technology and Innovative
Engineering, 2(7).

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Wun, T., Payne, J., Huron, S. and Carpendale, S., 2016, June. Comparing bar chart authoring
with Microsoft Excel and tangible tiles. In Computer Graphics Forum (Vol. 35, No. 3, pp.
111-120).
Yadav, S.K., Singh, S. and Gupta, R., 2019. Measures of Central Tendency. In Biomedical
Statistics (pp. 41-52). Springer, Singapore.