MIXED SIGNALS - Tilston · 2017. 6. 28. · Mixed Signals as the title of this paper is more than just a clever application of the usual saying, it underpins the paradox that surrounds

Jack Hughes ‘Mixed Signals’

Victoria Byrne September 2016 1

MIXED SIGNALS AN ANALYSIS OF THE MOBILE

PHONE SIGNAL COVERAGE IN

SAUGHALL

Jack Hughes

Victoria Byrne

September 2016



Acknowledgements

We are very grateful to a number of individuals without whose help this report would have not been

possible.

We would especially like to thank Michelle Collins for her innovative and sensible advice that helped

tremendously with our data collection methods. We would also like to thank Jessie O’Malley for her

support at the Saughall Farmers Market, as well as the many Facebook group admins who kindly

agreed to let us share the online survey link on their pages. Lastly, we are very grateful to the Saughall

and Shotwick Park Parish Council, and particularly Councillor Kathy Ford, Councillor Howard Jennings,

and Clerk Shirley Hudspeth, for keeping us up to date with any developments in this area and being so

cooperative with our report.



Contents

Preface ................................................................................................................................. 4

Summary ............................................................................................................................. 5

SECTION I ............................................................................................................................ 6 1.1 Introduction........................................................................................................................... 6 1.2 The Questions ....................................................................................................................... 7 1.3 Area and Subjects of Analysis .............................................................................................. 8 1.4 Asking the Questions ............................................................................................................ 9 1.5 Data Collection Methods .................................................................................................... 12

SECTION II ......................................................................................................................... 15 2.1 Foreword to Results ............................................................................................................ 15 2.2 General Findings ................................................................................................................. 15 2.3 The Hypotheses .................................................................................................................. 16 2.5 Closing Remarks ................................................................................................................. 26

Limitations ......................................................................................................................... 27

Clarifications ...................................................................................................................... 28

Appendix ........................................................................................................................... 30

Bibliography ...................................................................................................................... 36



Preface

This report is the product of a collaborative effort and seeks to examine the experiences of mobile

phone users in the village of Saughall.

Mixed Signals as the title of this paper is more than just a clever application of the usual saying, it

underpins the paradox that surrounds this issue. On the one hand we have the undertones of the

dissatisfied community crying out for change, while on the other we have those content with the

existing situation stating that things have changed. Whatever the reality, the mobile signal coverage

debate has been an enduring controversy within the village of Saughall. It has been a topic ripe with

deliberation and discussion at all levels, nonetheless, marginal headway has been made.

The purpose of this report is to shed some much needed light on the matter with the aim of arriving

at a progressive consensus. This will be done using statistical methodology backed up with tangible

evidence that will help to evaluate some of the opposing arguments that surround this issue. The way

in which this report will carry out this task is through two research questions:1) What is the signal

coverage like for the Village? and 2) How does the signal coverage affect certain age groups in the

Village? The data we obtain from this will help us to formulate some appropriate and coherent

recommendations, which may be used at the discretion of those with the power to implement them.

The work in this paper is aided by my background as a resident of Saughall and a student studying

social sciences at the University of Manchester. The motivation behind the research resides within a

mixture of personal interest in the topic and a frustration with the status quo.

Jack Hughes

September 2016



Summary

Saughall is an extremely desirable location with great transport links, a bustling nearby city,

and a supportive community network.

Two presumptive hypotheses will be made about the signal coverage in Saughall:

[HYP1] - Any individual using a mobile phone on any network in Saughall will suffer from poor

network coverage.

[HYP2] - Poor network coverage will impact a younger aged demographic group more severely

than an older aged demographic group.

We will ask an 8 question survey to 346 residents and non-residents in the Saughall area. This

is an appropriate sample size based on our statistical parameters and the approximated

population of the area.

We will obtain respondents through online and offline surveying methods. The online method

will involve an e-survey while the offline method will involve door-to-door surveying and

static surveying (surveying passers by).

From the 346 respondents that were asked, the most common response was ‘Very poor’ with

223 answers (64%), followed by ‘Poor’ with 79 (23%). This totals to 302/346 respondents

(87.3%) who said they had poor network coverage.

The worst network provider in our survey was Three with a 95% chance of the user

experiencing ‘Poor’ or ‘Very poor’ network coverage, shortly followed by O2 with a 91.7%

chance.

There is minimal evidence to suggest that poor network coverage always impact younger age

groups more severely.

In total, 82% of respondents said that their signal coverage was either ‘Problematic’ or ‘Very

problematic’ to their daily lives.

Overall, a staggering 98% of respondents answered ‘Yes’ when asked whether something

should be done about Saughall’s network coverage.

We recommend a number of measures to tackle these issues that are based around a

desirability framework. The First Best Solutions involve the installation of a mast and

discounted phone tariffs, the Second Best Solutions involve distributing booster technology

and more information for consumers, and the Third Best Solution involves greater recognition

of the problem.



SECTION I

1.1 Introduction The invention of the mobile phone is unquestionably one of our greatest achievements. Since Martin

Cooper’s grand unveil of the first handheld mobile telephonic device in 1973, mobile technology has

been revised, adapted and improved to make communication in each and every one of our lives 1

more accessible.

The advancements made in mobile telecommunications in the past decade have increased

exponentially with recent innovations in Smart Phone’s and 5G technology which will ripple into the

future. Over the next decade, there is little doubt that mobile phones will continue to become more

and more capable of carrying out the daily tasks that we would have otherwise carried out.

Nevertheless, if we trim back the embellishment, mobile phones are still unrivalled as convenient

methods of communicating with others around the world. They have and will continue to tear down

the boundaries of distance, help us to build stronger relationships, and bring us all closer on this

single planet.

The grand picture is however a topic for another day, and for us to continue would lead us astray and

beyond the scope of this paper. The purpose of this report is to assess the functionality of mobile

devices on a much smaller scale involving much fewer people, but do not let these last two points

trick you into underestimating the significance of this topic.

We will be focusing on the village of Saughall in this report. Saughall is located in the county of

Cheshire in the North West of England, it occupies a sizable piece of land and is home to over 3,000

residents and several small businesses. Its geographical placement is extremely well situated with

access to the M56 (for Manchester), the M53 (for Liverpool) and the M6 (for Birmingham) a matter of

minutes away. The nearest large settlement, Chester (a city of around 120,000), is a bustling,

expanding and historically rich city filled with heritage and things to do 2. The Roman Walls, Chester

Racecourse and Chester Cathedral alone bring hundreds of thousands of visitors from across the world

every year 3. Unity is at the heart of the Village with the Parish Council working diligently to ensure a

safe and thriving community. Saughall is without question an exceptionally desirable place to settle

down. Yet for all its merits, one persistent issue still plagues the area and its residents – poor mobile

network coverage.

This topic has the Village at an impasse and without the tools to form a coherent solution to the

problem, Saughall will remain locked into this stalemate. Depending on the results of our field

research, we hope our work can be used as a vehicle to crash through this stalemate and make some

headway on this issue. We will achieve this by employing the voices of those who have experienced

the signal coverage in the area, and it is now time for us to tell you how we are going to do this.

We plan to assess the coverage in the area through a dual analysis method: the first level (our primary

analysis) will look at how individuals experience their signal coverage and how certain networks fare

against others, while the second level (our secondary analysis) looks at how the coverage impacts

certain age groups (how their mobile signal coverage affects user’s daily lives). In order to obtain the

1 We now have more digital gadgets on this planet than we do people, see http://www.independent.co.uk/life-style/gadgets-

and-tech/news/there-are-officially-more-mobile-devices-than-people-in-the-world-9780518.html 2 Chester has been nationally recognised last year in the UK Hot Housing Index as the best place to live in the UK, see

http://www.chesterchronicle.co.uk/news/chester-cheshire-news/chester-named-top-place-live-10103325 3 See the following link for detail, http://www.chesterchronicle.co.uk/news/chester-cheshire-news/tourism-boost-cheshire-

record-visitor-9753702

http://www.independent.co.uk/life-style/gadgets-and-tech/news/there-are-officially-more-mobile-devices-than-people-in-the-world-9780518.html

http://www.independent.co.uk/life-style/gadgets-and-tech/news/there-are-officially-more-mobile-devices-than-people-in-the-world-9780518.html

http://www.chesterchronicle.co.uk/news/chester-cheshire-news/chester-named-top-place-live-10103325

http://www.chesterchronicle.co.uk/news/chester-cheshire-news/tourism-boost-cheshire-record-visitor-9753702

http://www.chesterchronicle.co.uk/news/chester-cheshire-news/tourism-boost-cheshire-record-visitor-9753702



data required to assess these objectives, we will carry out a comprehensive survey of the area that

when coupled with some data analysis we will be able to look into the general experiences of signal

coverage in the area.

We think that it would be beneficial to the reader to consider this report in two sections: Section I

covers introductory material, our hypotheses/presuppositions and how we plan to carry out our

research, Section II focuses on the results of our research and the recommendations we make based

on them.

As mentioned, this section will contain some presuppositions that will help with later comparisons and

structure. Before our field research is conducted we are therefore presupposing two hypotheses:

[HYP1] - Any individual using a mobile phone on any network in Saughall will suffer from poor network

coverage.

[HYP2] - Poor network coverage will impact a younger aged demographic group more severely than an

older aged demographic group.

The consequences and recommendations of this report will be shaped by the results of our field

research. This means that the validity of these hypotheses will be tested against and compared with

the data we collect.

With the introductory material out of the way it is now appropriate to move onto the questions that

we will be asking.

1.2 The Questions The questions that will be asked in our survey are designed around our two hypotheses (HYP1 and

HYP2). These hypotheses produce two questions: the first question is whether Saughall really does

have poor network coverage and whether that coverage is exclusive to certain providers? The second

question is how does the network coverage impact certain age groups?

As discussed, we intend to answer these questions through a survey designed to provide us with

adequate data to make the necessary inferences. The survey we have opted for is a short, 8 question

survey (a copy of which can be seen in the Appendix, Figure 1).

We will now go through each of the questions briefly (Q) and the reasons (R) that we have chosen to

ask them:

Q1) (Q) What is your road name and number? (R) This question will help us to determine

how widespread poor signal coverage may be. We also think that recording road names

(and numbers) enables us to obtain our data more fairly by covering each road as equal

as possible. Lastly, if we need to return to a certain road for more data, we can avoid the

houses who have given us their numbers.

Q2) (Q) How would you rate the signal coverage for your mobile handset when using it

within the Saughall area? (R) The answers to this question will help us to determine our

first level of analysis. It will also enable respondents to share their experience of the

mobile phone signal coverage.



Q3) (Q) How consistent is the signal coverage for your mobile device within the Saughall

area? (R) Similarly to Q2, this will help to answer our first level of analysis.

An important note must be made about this question in particular (Q3). We actually chose

not to use the data from this question in our analysis in Section II. The reasoning for this

was that we noticed its incompatibility with Q2 too late and we were unable to account for

poor wording of the question. This incompatibility can be seen when answering ‘Mixed’ for

Q2, which practically voids the consistency question. Furthermore, two of the answers in Q3

(‘Mixed’ and ‘Inconsistent’) are virtually synonymous making the question confusing for the

respondent. Lastly, we felt this question was unnecessary; Q2 covers the consistency element

as users undoubtedly will already be factoring in signal consistency when deciding how to

rate their coverage.

Q4) (Q) Who is the provider of your mobile device signal? (R) This will allow us to

determine whether poor signal coverage is limited to certain providers. It will prove

helpful for when we come to making recommendations as we may be able to advise

residents (current and potential) which networks to avoid.

Q5) (Q) What is your age range? (R) The answers to this question are important in unison

with the following question to help answer our secondary level of analysis.

Q6) (Q) How would you rate the impact of the mobile signal service on your day-to-day

life? (R) Coupled with an age range from Q5, we can determine how the network

coverage may impact certain age groups from the responses to this question.

Q7) (Q) Do you have a landline? (R) The answers to this question helps us to develop on our

secondary level of analysis.

Q8) (Q) Broadly speaking, do you think something should be done about the mobile

phone signal coverage in the Saughall area? (R) This last question concludes the

survey. It does not specify the means by which change could be achieved, but users

answering ‘Yes’ clearly would demand something to be done. We feel a direct question

like this is necessary when it comes to formulating a consensus.

We will now move onto the area we wish to assess and the individuals we plan to survey.

1.3 Area and Subjects of Analysis

Now we have determined what questions we are going to ask and the reasoning for them, it is

appropriate to be more specific about who we are going to ask. It should already be clear to the

reader at this point that this report focuses explicitly on the village of Saughall; it therefore does not

concern the surrounding areas such as Mollington, Shotwick Park, Etc., (but this is not to say that the

findings may not be common amongst residents from these other areas). We would certainly like to

assess a larger area, however it is more realistic to constrain our field research to a single designated

place. There are many good reasons for doing this, such as a lack of resources, but more importantly

we feel focusing on a single place means we can be more thorough in our analysis.

To ensure that we are clear about the area we are assessing we have included a mapped diagram

which can be found in the Appendix, Figure 2. In the diagram our area of analysis is contained within



the drawn boundary, meaning any external locations are not to be included in our survey. It is now

important for us to elaborate on the subjects of analysis, which is a more complicated issue.

We could reserve our investigation to just permanent residents of Saughall, however we believe the

true longevity of residence does not matter greatly when considering what we are assessing. It is true

that a long-term, permanent resident and mobile phone user would have more experience of the

signal coverage in the area, but we are more concerned about the general experience of any users in

the area, be it visitors, long-term or new residents. While we anticipate that the majority of responses

will come from permanent residents, we are expecting several to not be, but this does not impact our

analysis by any significant degree, if anything, a view from an externally located individual is valuable

for the user would have experience of both places and be able to make a sound judgment.

1.4 Asking the Questions Up to this point we have discussed some of the key preliminary elements for this report, and it is now

time for us to be more explicit about the amount of individuals we will be surveying. This part of the

report does contain some of our statistical methodology but we shall clarify any necessary subject

material, so this should not seem daunting to the reader.

As mentioned previously, in consideration of time and resource constraints, we have chosen (as many

statistical agencies do) to survey a representative sample of the population. The key word in that last

sentence is representative; we are looking to obtain a sample that tells us certain things about the

population as a whole. An analogy may be helpful for visualisation: imagine a sandwich, you would

like to know what the whole sandwich tastes like without eating it all, so you take a small bite with the

hope that you will taste all of the contents in the single section. How much that bite resembles the

whole sandwich is a measure of representativeness. In the same way that you would not choose to eat

a section with nothing in, we would not take a survey from a single network provider on a single road

and generalise about all providers and all roads, for example.

There are four things that we must determine in order to calculate our sample size, and now would be

a good time to briefly familiarise ourselves with them:

1) Confidence level: A confidence level is a number which tells us how many times we think our

survey results would fall within a parameter (range) of the total population (if they were

surveyed) if we conducted the survey over and over again. For example, a 95% confidence

level tells us that if we completed that survey of the population 100 times, in 95 of those cases

our survey data would fall within a parameter of the population (the parameter is made more

clear in the next point).

2) Margin of error (confidence interval): This is the parameter that was discussed in the previous

point; it is a range given as a plus or minus number (i.e. +/- 10%, +/- 5%, +/- 1%, etc.). The

choice of number depends on how accurate we want our sample to be (or how much

inaccuracy we would allow) as no sample will perfectly represent the population. The more

accurate we want to be, the smaller the margin of error and the less the answer deviates from

the population. The smaller the margin of error, the larger the sample size has to be to ensure

accuracy (however a balance must be struck between a sensible sample size and the accuracy

of data, as a general rule most statistical agencies and outlets will use a margin of error of

5%). When this is combined with (1) the confidence level, we get a spread, e.g. we would



expect our sample results to be +/- 5% (margin of error) within the population 95%

(confidence level) of the time 4.

3) Response distribution: this is used to predict the variability of answers in the survey. In one of

the questions if we obtained results of 99% ‘Yes’ and 1% ‘No’ then the error is minimal.

However, if the chances of either answer were 51% and 49% then the chance of our error

increases. As we don’t know what the answers will be as of yet, we must use the safest value

of 50%.

4) Population size: the total amount of individuals that are within the area that we are measuring

and related to the subject we are assessing. For example, if we were doing a report about dog

walkers in the North West, our population would be the total number of dog walkers in the

North West 5.

For (1) and (2) we will be using a margin of error of 5% and a confidence level of 95%. These are

industry standards and they mean that our survey data will fall between +/- 5% of the population in

95% of the cases. For (3) we will be using a response distribution of 50%, so all that is left is for us to

calculate our population size as accurately as possible.

Determining the population size of an area is no easy task; we feel the most sensible way to go about

this is to use data from the Office for National Statistics (ONS) (the largest producer of statistical data

in the UK) for the most recent population size for the village. This is given in the 2011 Census and is

calculated to be 3,009 (Office for National Statistics , 2011). As we are looking to obtain the most

accurate results possible, it would be unfair for us to assume this population has remained static since

that date. We will therefore be using this population size as a basis for our adjusted population.

With an absence of more recent data we feel the most rational way to progress is to assume that the

population of Saughall has risen in the past 5 years. The first step we shall take is to increase the 2011

Census base data in line with the average population increase in England (where the village is located)

over the same period (2011-2016). Using population estimates (Office for National Statistics , 2016), a

simple calculation will tell us that in the last 5 years, from 2011 (Census year – 53,107,200) to 2015 (last

year – 54,786,300), that the population in England has increased by around 3.2%. Taking this result, we

can apply it to our Census data giving us a new approximate resident population of 3,106 people.

The next logical step would be for us to look at who may have migrated into the area in the last five

years. New residents living in the area will almost likely be housed, meaning it is most appropriate to

consider any recent housing developments in that five-year period. Our research has brought up three

in particular:

28 6 new properties built by Morris Homes in Willow Hey (opposite Rakeway) on the old site of

The Riding’s infant-school that was closed down in 2009.

18 7 new properties were completed last year on Thomas Wedge Road (just off Lodge Lane).

4 If you are still unsure about confidence levels and margins of error, here are some helpful links that explain it in a very

simplistic way (and probably much better than we do):

http://www.statisticshowto.com/confidence-level/

http://www.dummies.com/education/math/statistics/how-to-interpret-the-margin-of-error-in-statistics/

https://www.youtube.com/watch?v=NH40E65TWqg 5 Because of the difficulties involved in determining such a figure, populations are often approximated. 6 Taken from the Morris Homes website stating a new development of three and four bedroom detached and semi-detached

properties, see http://morrishomes.co.uk/news/2013/october/morris-homes-opens-new-saughall-development/ 7 This quantity was counted by us but confirmation can be found in the Saughall and Shotwick Park Parish Council Chairman’s

Annual Report (2014/2015) (pg.4) http://www.saughall.gov.uk/wp-content/uploads/2015/03/Chairmans-Report-2015.pdf

http://www.statisticshowto.com/confidence-level/

http://www.dummies.com/education/math/statistics/how-to-interpret-the-margin-of-error-in-statistics/

https://www.youtube.com/watch?v=NH40E65TWqg

http://morrishomes.co.uk/news/2013/october/morris-homes-opens-new-saughall-development/



3 8 new properties were completed in 2015 on Hermitage Road.

(High Grove, a large housing development large built by Antler Homes on the site of the old

railway station (Seahill Road), was constructed in late 2008 9 and so we shall assume that new

residents were included in the 2011 ONS survey and will make no attempt to inflate the

population in relation to this development)

These three developments are all contained in the last five years meaning that we must account for a

further 49 households in our population estimate. To determine how many individuals this translates

into we can once again refer to the 2011 Census for the area; the data tells us that there were 1,265

(Office for National Statistics , 2011) households in the area. Taking this figure and adding our 49 new

households we get an updated figure of 1,314. Using this figure again we can divide our adjusted

population size of 3,106 by the new households figure to find that there is approximately 2.4 residents

per household. Multiplying the household average by the 49 new homes we get a figure of

approximately 118 new residents. We feel this is the fairest way to calculate the new population of this

households without physically questioning each of them. Adding this figure to our previously adjusted

population estimate we get a new population of 3,224 which will undoubtedly be closer to the true

population.

We recognise that this result could still be an underestimation of the true population and so we will

take one final measure to ensure our population is fairer. We will add a 5% margin on top of the

adjusted population based on current statistics. The results of which could pose two questionable

scenarios, both of which are still positive as we explain:

1) What if the 5% margin still meant that we fall short of our true population? This is still a

possibility, however, it will put us closer to the true population so it is a sensible calculation.

2) What if the 5% margin puts us over the true population? Again this is a possibility, however it is

a much more desirable situation to overestimate than to underestimate. Because our soon to

be calculated sample size is linked to the population (they rise together), overestimating the

population would only lead to a larger necessary sample size. In any case a larger sample size

than is required will only lead to more accurate results.

In light of these apprehensions adding this 5% margin should account for any new households we did

miss or any errors in our calculations. A 5% margin equates to 162 new residents (rounding up), which

when added to our adjusted Census population gives us a final population estimate of 3,386.

Now that we have our population size, we can use the aforementioned calculations to work out an

appropriately representative sample size. With a population of 3,386, a margin of error (confidence

interval) of 5%, a confidence level of 95% and a response distribution of 50% we calculate that an

appropriate sample size would have to be 346 individual respondents.

All that is left to discuss about this sample size is how we will distribute it across the area as fairly as

possible. We have created a list of roads from our designated area, which can be seen in the Appendix,

Figure 3. The list shows that there are a total of 49 roads in the area 10 which we will use to guide the

8 This quantity was physically counted by us 9 The most accurate log of the development dated http://www.easier.com/39697-the-perfect-gift-a-new-home-at-high-grove-

in-saughall.html 10 This list was constructed using another list as a basis which can be found here:

http://www.geographic.org/streetview/uk/Cheshire_West_and_Chester/saughall.html). We adjusted this list by working through

and making sure that all roads were located in the area before adding any new roads that have been created such as Thomas

Wedge Road and Willow Hey.

http://www.easier.com/39697-the-perfect-gift-a-new-home-at-high-grove-in-saughall.html

http://www.easier.com/39697-the-perfect-gift-a-new-home-at-high-grove-in-saughall.html

http://www.geographic.org/streetview/uk/Cheshire_West_and_Chester/saughall.html)



distribution of our survey data. Dividing 346 (sample size) by 49 (number of roads) we get around 7

respondents per road. We will use this as a guide to determine the amount of respondents to take

from each road. However, we can envisage a number of issues with this method: certain roads that do

not have 7 respondents, where we find it impossible to obtain this many, or where we obtain more

respondents than is necessary. In these cases, we will have no choice but to proceed with obtaining as

many respondents as necessary. We will use the 7 per road guide to ensure that through our door-to-

door methods we will not ask more respondents from a road that we have already obtained 7

responses for, furthermore we will actively seek to obtain more respondents for roads which we have

not obtained 7 from. In most cases, this guide will help to safeguard against over-representation and

underrepresentation of certain roads. In our other methods of surveying (offline and online, which we

will soon speak about), we will be unable to guarantee a 7 per road quota. Overall however, we will be

seeking to obtain respondents from each road on the list as we feel this does adequately cover the

village entirely.

We shall now move on to how we intend to obtain these results.

1.5 Data Collection Methods There are two main avenues by which we plan to obtain our data: offline and online surveying.

Offline surveying can be split further into two areas: door-to-door and static surveying. Door-to-

door surveying will involve us making our way round the entirety of the village seeking to obtain

a set amount of residents from each road. Surveys will be done face-to-face with the answers

given by the individual/s in the household/s and the data recorded by one of us on the survey

sheets. The second offline method, static surveying, involves us being present in a certain

location for a period of time during which individuals will be asked by us if they would like to

complete the survey, or they may approach us to do so. There are two particular locations where

this will be carried out: 1) the Saughall Farmers Market (a regular gathering in the Vernon Institute

(the Village Hall) of buyers and local sellers of meat and produce), and 2) the Saughall All Saints

school pick-up. Both these locations and time periods have two beneficial things in common:

they have ways in which we can announce our intentions beforehand, and they are both

occasions when many individuals will be present in one place. Both of these things help us to

spread awareness about this issue as well as ensuring that we can obtain a lot of respondents.

The second avenue of data collection is online and will be done through an e-survey on

Kwiksurveys. Kwiksurveys is a powerful surveying tool that offers real-time data analysis and

presentations and is used by many large organisations such as the BBC and NHS 11. The online

survey will mirror that used in the offline collection except it will not record road numbers (to

allow this feature we would have to pay a premium which is beyond our budget). The survey can

be accessed via an online link which will be posted in several groups on Facebook. These groups

will be selected to ensure that we are not appealing to the wrong audience, and will often be

placed in groups closed to non-Saughall residents. The answers to the e-survey will relate to a

single respondent, but it will be made clear that if households wish to express multiple views that

this can be done through multiple surveys.

It would be important now to discuss how we will make these methods random. Randomness is

important for making the sample representative and to be fair to the overall results. Randomising

a sample is not a simple endeavour, but we feel that by their very nature, our survey methods are

inherently random. Online, the e-survey is random as we have no idea who will see the link and

who will complete the survey. Similarly, the offline static surveying will also be random as we

11 Logos of these organisations appear on the Kwiksurveys website, see https://kwiksurveys.com/

https://kwiksurveys.com/



have no way of knowing who will attend the event. In terms of door-to-door surveying, we will be

using a random number generator to randomise houses on each road. The number generator will

be completely random and we will use the generated number to determine which houses to

knock on, i.e. a number 5 means we will call at every fifth house on the road.

We have now considered all the necessary steps preceding our survey, so it is now time for us to

conclude Section I and to progress into Section II to look at our results.





SECTION II

2.1 Foreword to Results

We have now completed our survey and are pleased to say that we have met our target of 346

respondents.

We began our data collection on time and as intended operating through both online and offline

avenues. Both survey methods were very well received and respondents were keen to express their

views; we thank each and every one of you who completed the online or offline survey. It was a

wonderful experience meeting so many interesting characters with countless fascinating stories about

their experiences.

The online survey was posted in Facebook groups that related to the area 12 and many of which were

closed subject to admins approval. Admins were asked beforehand if we were able to do this and all

of them were very cooperative.

All of the findings from both the online and offline surveying were recording and analysed using the

same program, Microsoft Excel 13. Kwiksurveys does offer some analysis tools but we felt this was

unsuitable as it was only able to analyse the online responses.

2.2 General Findings We will begin our analysis with a general breakdown of the findings:

These 346 respondents come from all 49 roads in the Saughall area as well as from three

external locations, Blacon, Mollington and Connah’s Quay 14.

The most common signal coverage rating was ‘Very poor’ with a total of 223 responses (64%).

Data was collected from over 12 different network providers, but 5 of these providers (O2, EE,

Vodafone, Tesco Mobile and Three) accounted for 91% of the results.

The worst network provider was Three with a 95% chance of user’s experiencing ‘Poor’ or ‘Very

poor’ signal coverage. This was shortly followed by O2 with 91.7% (with a 72.2% chance of this

being ‘Very poor’)

12 You can see these posts and the pages they were posted on here:

- https://www.facebook.com/groups/532494326910779/permalink/611520845674793/?comment_id=6115845156

68426&ref=notif&notif_t=group_comment&notif_id=1472842203946480


1840208&reply_comment_id=1249432545102084&ref=notif&notif_t=group_comment&notif_id=147291856769

6298


1840208&reply_comment_id=1249432545102084&ref=notif&notif_t=group_comment&notif_id=147291856769

6298





13 If anybody would like a copy of this data we would be happy to share it with you, please email [email protected]

under the subject ‘Data Request’ 14 1 respondent was recorded from each of these external locations with the exception of Mollington which had 2.

https://www.facebook.com/groups/532494326910779/permalink/611520845674793/?comment_id=611584515668426&ref=notif&notif_t=group_comment&notif_id=1472842203946480


https://www.facebook.com/groups/833759223336087/permalink/1248293068549365/?comment_id=1248717971840208&reply_comment_id=1249432545102084&ref=notif&notif_t=group_comment&notif_id=1472918567696298










mailto:[email protected]



We obtained respondents from all of our questioned age brackets, but the most common age

range was our mid age bracket of 25-45, shortly followed by our mid-old bracket 46-65, both

of which account for just short of 75% of responses.

In total, 82% of respondents said that their signal coverage was either ‘Problematic’ or ‘Very

problematic’ to their daily lives.

Overall, a staggering 98% of respondents answered ‘Yes’ when asked whether something

should be done about Saughall’s network coverage.

Now we have considered these general points, we can begin to look at the data more intricately and

in relation to our two hypotheses.

2.3 The Hypotheses

We will now look at the data in relation to our initial presumptions to compare and contrast. This will

help to structure the section as well as demonstrating our findings.

Hypotheses One (HYP1)

Any individual using a mobile phone on any network in Saughall will suffer from poor

network coverage. For this hypothesis we must look more closely at the answers obtained in Q2 and Q4 in the survey. As

mentioned we will no longer be assessing the data from Q3 despite its relevance to HYP1.

We shall first examine the

results from Q2 and see

how the respondents

rated their mobile signal

coverage.

Out of the 346

respondents that were

asked, 223 (64%) said

that their mobile signal

coverage was ‘Very poor’

(making this the most

common answer), and a

further 79 (23%) said that

their mobile signal

coverage was ‘Poor’. In

total this equates to a

staggering 302/346

respondents (87.3%) who

said they had poor signal

coverage. These results

are modelled in Figure 4

to the right with the

different answers

4%8%

23%

1%64%

Signal Coverage Rating

Good

Mixed

Poor

Very Good

Very Poor

Figure 4



represented by different shades of blue. A quick glance will tell us how large the share of results went

to the ‘Very poor’ and ‘Poor’ responses.

Only 14 (4%) respondents rated their signal coverage ‘Good’, while just 3 respondents (<1%) rated

their signal coverage ‘Very good’. The remaining 27 respondents (8%) said their signal coverage was

‘Mixed’ (sometimes good and sometimes poor). These last figures are dwarfed by those rating the

signal coverage poor which demonstrate that only an extremely small minority can be considered

reasonably content with their signal coverage.

The way in which our sample was calculated (see 1.4) means we can make some statistical inferences

about the total population based on this data.

We are therefore 95% certain that these results will fall within +/- 5% (margin of error) of the true

population values. This means that the percentage that said their connection was ‘Very poor’ will

range between 59% (64% - 5%), and 69% (64+ 5%) in 95% of the cases. Similarly, the percentage of

individuals who would rate their coverage ‘Poor’ will range between 18% (23% - 5%) and 28% (23% +

5%). From these calculations we can determine that 95% of the time we will obtain a minimum ‘Poor’

signal coverage response rate of 77% (minimum values added), and a maximum ‘Poor’ signal coverage

response rate of 97% (maximum values added). These minimum and maximum values present a

hugely negative perception of the signal coverage in Saughall. In consideration of HYP1, we cannot

guarantee that a device user in Saughall will always have poor network coverage, but we can say

based on these results that the overwhelming majority will.

We will now move on to the second part of the hypothesis and look more specifically into how certain

networks fare.

Due to the limited scope of this report, we will confine our analysis to the top 5 mobile providers

which accounted for 91% of the respondents: O2, EE, Vodaphone, Three and Tesco Mobile. Our

hypotheses states that poor network coverage will be experienced on any network provider. In this

instance then it does not help to generalise the networks but to be more specific about how they are

individually. We can obtain this data by looking at conditional probabilities. A conditional probability is

the probability of one event occurring (A) given another event has occurred (B). For example, suppose

we wanted to look at the probability of a device user having ‘Good’ signal coverage given that they are

on O2, we can do this by using a conditional probability which tells us the chances of having ‘Good’

signal (event A), given that they are on O2 (event B). The mathematical notation for calculating

conditional probabilities is as follows:

𝑃(𝐴|𝐵) = 𝑃(𝐴 ∩ 𝐵)

𝑃(𝐵)

Although this may seem a little daunting, once explained and broken down it is actually very simple.

The left hand side of the equation (P(A|B)) is our conditional probability formula and can be read as,

“The probability (P) of event (A) occurring, given (|) event (B) has already occurred.” For example, the

probability of rolling a 3 on a dice, given that we have already landed heads on a coin.

Where P = Probability

A = Event A

B = Event B

∩ = Intersection/and

| = Conditional on



As we can see, the = sign tells us that this is given by the right hand side of the equation, in other

words the fraction on the right hand side equals our conditional probability. The top half of the

fraction (P(A∩B)) can be read as, “The probability (P) of event (A) occurring and (∩) event (B) occurring.”

This is what’s known as a joint probability (the probability of two events occurring at the same time).

For example, the probability of rolling a 3 on a dice and landing a heads on a flipped coin.

This is not to be confused with our conditional probability which assumes that one event has or will

occur and then looks at the probability of the other occurring (A given B), while a joint probability

simply looks at the probability of them both happening (A and B) at the same time.

Lastly, we have the bottom half of the fraction on the right hand side. This is a marginal probability

and is the most straightforward of all of these probabilities. It is simply the probability of one event

occurring. For example, the probability of rolling a 3 on a dice.

With this understood 15 we can look at the equation as a whole which may be read as, “The conditional

probability of event A given event B equals the joint probability of event A and event B divided by the

marginal probability of event B occurring.” To find the answers we are looking for in relation to HYP1,

all we need to do is substitute our data into the equation.

We are now able to look at the best and worst network providers using our probabilities as an analysis

frame. We will look at the conditional probability of having a certain level of signal coverage (‘Good’,

‘Poor’, etc.) given that we are on a certain network provider (O2, EE, etc.).

Conditional Probability Signal Coverage Rating

Network Very Good Good Mixed Poor Very Poor

Total Poor

(Poor and

Very Poor)

Total Good

(Good and

Very Good)

Three 0.0% 5.0% 0.0% 35.0% 60.0% 95.0% 5.0%

O2 1.5% 2.3% 4.5% 19.6% 72.2% 91.7% 3.8%

Tesco Mobile 0.0% 0.0% 10.5% 21.1% 68.4% 89.5% 0.0%

EE 0.0% 5.6% 10.1% 24.7% 59.6% 84.3% 5.6%

Vodaphone 1.9% 3.8% 17.0% 18.9% 58.5% 77.4% 5.7%

These results can be seen in the table below (Figure 5) and were calculated using our survey data. We

followed the sample methodology that was mentioned before to determine all of these results.

Across the rows we have network providers (the 5 that we will be focusing on and that make up 91%

of our survey) and down the columns we have our signal coverage rating. In the boxes is the

conditional probability that you obtain that level of signal coverage (down the column) given that you

are on the provider (across the row).

A brief glance will tell us that the worst network provider is Three, with a total poor probability (the

probability of having ‘Very poor’ or ‘Poor’ network coverage) is 95% (which can be understood as

having a 95% probability of having poor network coverage given that you are on the network Three).

This is shortly followed by O2 which has a lower total poor rating of 91.7% but the highest result for

‘Very poor’ at 72.2%.

15 If these probabilities are still confusing to the reader, here are some helpful explanations:

http://sites.nicholas.duke.edu/statsreview/probability/jmc/

http://www.investinganswers.com/financial-dictionary/ratio-analysis/joint-probability-3379

Figure 5

http://sites.nicholas.duke.edu/statsreview/probability/jmc/

http://www.investinganswers.com/financial-dictionary/ratio-analysis/joint-probability-3379



Conversely in our list we have the best networks to be on (a term we use lightly). The network with the

highest probability of a good network coverage is Vodaphone at 5.7% (also the most likely to be ‘Very

good’) shortly followed by EE at 5.6%.

These results demonstrate a bleak picture for the 91% 16 of respondents that are on these networks

with very many at an extremely high chance of poor signal coverage, and a very low chance of good

signal coverage.

Conclusion

Our hypothesis (HYP1) stated that any user on any network will suffer poor signal coverage. While

HYP1 does not hold for the small amount of respondents that said their signal coverage was not poor

(13%), or for the 7 networks which had respondents who said they had ‘Very good’, ‘Good’ or ‘Mixed’

network coverage, the data shows a clear network coverage endemic adversely affecting those using

mobile devices in Saughall.

An 87% response percentage for users saying they had ‘Poor’ or ‘Very poor’ network coverage coupled

with the best network having just over a 1 in 4 chance of having ‘Good’, ‘Very good’ or ‘Mixed’ network

coverage is simply not acceptable for active paying users of these devices.

Amongst the 87% of users who experience poor network coverage are business users who rely on the

use of their mobile phones to communicate with clients and customers around the country. There are

also individuals in danger of life-threatening accidents who would need to contact emergency services

at any point. With these results, mobile device users in Saughall have virtually no network they can

turn to for an acceptable and reliable service, and for anyone in the aforementioned circumstances

this is a very dangerous reality indeed.

We feel that intertwined within this data is a cogent and poignant argument for improving the

network coverage in the area.

16 The other 9%, while not included, we can assure do not fare much better.



Hypotheses Two (HYP2)

Poor network coverage will impact a younger aged demographic group more severely

than an older aged demographic group.

In assessing the validity of this hypotheses we will be focusing on the data obtained from Q5 (age

ranges), Q6 (the daily impact of the signal coverage) and Q7 (whether respondents have access to a

landline). The hypotheses states poor network coverage which means our analysis will also make use

of the answers from Q1 who answered ‘Very poor’ or ‘Poor’.

Across the data, 302/346 (87.3%) said they had ‘Very poor’ or ‘Poor’ network coverage. Looking at this

group (those who rated their network coverage ‘Very poor’ or ‘Poor’), 77.8% (77.8% of the 87.3%/a

percentage of a percentage) said that this was either ‘Very problematic’ or ‘Problematic’ to their daily

lives. In consideration of our hypotheses, we need to look at how this data plays out across different

age groups.

Figure 6

Figure 6 is a helpful representation of how the data played out. Before looking at the data, it is helpful

to explain what each of the axes represents. On the left side we can see progressively increasing

percentages under the heading ‘Severity’. Severity in this case represents the amount of individuals

with ‘Poor’ or ‘Very poor’ signal coverage who said this was ‘Problematic’ or ‘Very problematic’ to their

daily lives. On the horizontal axis we have the age ranges that were included on the survey. To break

this down further, it is helpful to explain some of the data on the diagram. As we can see, the first

input is the age range of <16 with a severity of 100%. This means that all of the <16 range

respondents who had ‘Poor’ or ‘Very poor’ network coverage said this was ‘Problematic’ or ‘Very

problematic’ to their daily lives (i.e. maximum severity).

We will now assess how the data fits on the diagram. There are three lines to explain: the broken line

represents our expected results based on HYP2 which illustrates a steadily declining severity as age

100.0% 89.3%91.0% 91.2%

75.6%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

<16 16-24 25-45 46-65 66+

Seve

rity

Age Range

Severity of Poor Singal Coverage by Age Range



increases. The solid black line models the data that was recorded in our research. Lastly, the green line

represents the trend of our research data (displayed on the black line).

We will first speak generally about the diagram and then be more specific about the age ranges.

A quick glance will tell us that that our expected results were not as severe as our true results. The true

results do decrease to begin with but levels off and even increases before falling once again. The

trend line (green arrow) does support HYP2 demonstrating a falling trend in severity as age increases,

however the gradient of this line is much shallower than we would have expected from HYP2 (the

broken line).

We shall now look at how the data progressed in relation to the hypotheses. Firstly, both the expected

and true data support HYP2 at our initial youngest age demographic (<16) of which 100% said a poor

network coverage is ‘Problematic’ or ‘Very problematic’ to their day to day lives. As we move onto the

older age range of 16-24, severity falls further to 89.3%, and while this is not as much as our expected

results, it does still support HYP2. We then have an increase to 91% in 25-45 age bracket and a further

increase to 91.2% for the 46-65 age bracket. While these results are not as severe as our <16 age

range, they are worse than the 16-24 range and thus work against HYP2 (which would have expected

further drops in severity, not increases). Following the 46-65 range, we do have a second drop to

75.6% for our 66+ age bracket; this again is in keeping with HYP2 but is by no means close to our

expected results for the age range of around 20%. Our trend line shows that as we move in the 66+

age range, severity does not fall by the amount we expected.

While our general trend line does support HYP2 to some extent, the individual results for the age

ranges are not as consistent as we expected. Our results do show that the <16 range suffered the

most severe impact overall but this is shortly followed by the 46-65 and 25-45 age groups, while older

than the 16-24 group they demonstrate an increase in severity. In terms of an explanation for these

results, there are potentially a lot of business users within these age brackets, who may be heavily

reliant on their device for business use (meaning a poor signal would be very problematic/severe).

One thing that cannot be disputed is the level of severity across all age groups; while the results do

fluctuate, they remain at a high level across the board. This does suggest that a poor network

coverage will more than likely be problematic to the individual irrespective of their age range, and

thus it must be recognised that the severities of poor signal coverage are not restricted to certain

ages.

One last thing to look at before concluding this section is the answers we obtained from Q7 on

whether respondents had access to a landline. From our survey we found that the mass majority of

respondents had access to a landline (96.2%), while only a handful did not (3.8%). What is interesting

here is the amount of each group who said this was still an issue to their daily lives. We would expect

that those without access to a landline would find poor network coverage an issue, and rightly so with

92.3% (of those without a landline) stating that this is either ‘Problematic’ or ‘Very problematic’. What

we also expect is for those with landlines to be the only group to state that poor network coverage

has ‘Little impact’ or even enhances their daily lives, except only a small fraction of this group did so.

Just 17.6% of those with landlines said that a poor network coverage for their mobile phone ‘Enhances

Daily Life’, or has ‘Little impact’ or ‘No affect whatsoever’. The remaining 82.4% of this group said that a

poor network coverage was still ‘Problematic’ or ‘Very problematic’ despite having access to a landline.

This demonstrates that even when alternative methods of communication are available, a functioning

mobile phone is much more desirable and superior as a method of communication. Our conclusion

from this should be that access to landlines will not in the majority of cases, alleviate the troubles

associated with a poor network coverage for a mobile phone.



Conclusion

These results support HYP2 generally, but individually they are not as forgiving. The young-mid age

ranges of 25-45 and 46-65 are contrary to our expectations; this is an important observation as it

helps to break down a common misconception that the younger you are the more severe poor

network coverage will be to your daily life. Across the board poor networks coverage does largely

result in problems for device users across the area. We should therefore not restrict our approach to a

certain age group, nor hide behind the excuse that the area is dominated by one. We must recognise

the severe impact this has on all age ranges and to not assume that the elderly does not suffer in a

similar way to younger aged groups. We should also not presume that users with access to landlines

do not mind having poor mobile network coverage, as demonstrated by the many with access to

landline who still state that a poor network coverage is an issue to their daily lives.

2.4 Recommendations

There are many important sections in this report each with their own independent value, however, out

of all of them this is the most significant to our efforts and we hope that it is the most referred to.

We are now about to make some recommendations based on our analysis of the data. These

recommendations are motivated by the results we have obtained and the interpretation/analysis we

have just done. We use the term recommendations as opposed to intentions because we ultimately are

not the body with the capacity to carry them out. Instead, we are confident that these suggestions will

be taken seriously by those who do possess this capacity and we hope that the majority of them will

be acted upon.

We will be organising these recommendations into three categories, First Best Solutions, Second Best

Solutions and Third Best Solutions. They are in order of the impact we predict them to have on the

signal coverage issue in the area, but this is not to be confused with an order of desirability as we

strongly believe that all these solutions are desirable in their own right.

There will of course be additional untouched-points/counter-arguments made about these

recommendations and we thoroughly intend for them to be brought under scrutiny and open

discussion to ensure that all things are considered in a fair and compromising manner.

First Best Solutions

We recommend the installation of a new phone mast within, or nearby, the area

that will boost the signals of all, or certain, mobile networks

Out of all of these recommendations, this will undoubtedly be the most expected, logical and

impactful (and almost certainly the most contentious). Based on our results, it is apparent that the

network coverage issue in Saughall is a serious endemic. Mobile phones require phone masts to

communicate and transmit calls and messages (in the form of electromagnetic fields or EMFs). A new

mast in the area will improve signal coverage for users which will be the most necessary and

important step towards tackling the issue. We do of course understand the many arguments against

the installation of phone masts and we shall take just a few of the popular ones to give our response:



1) They pose health risks

We would like anyone with this apprehension to consider the following reports that have

conducted large scale, heavily-funded research into this area:

The Mobile Telecommunications and Health Research Programme has released two

reports in 2007 17 and 2014 18 (completed in 2012) which collate a mass collection of

data that finds no apparent association between mobile phone usage and health

risks.

The independent Advisory Group on Non-ionising Radiation (AGNIR) released a report

in 2012 19 that looked into the health effects associated with mobile phones and

electromagnetic fields (EMFs) (the means by which mobile devices communicate). In

short, the conclusions were again that there have been no detectable health risks

associated with exposure to EMFs.

The Million Women Study 20 was conducted in partnership with Cancer Research UK,

the National Health Service (NHS), and researchers at the University of Oxford. This

joint effort has also found no evidence to suggest that mobile phone usage has any

impact on the chances of developing certain types of cancer.

These reports demonstrate a strong consensus within the field of study that mobile

phone usage does not pose any noticeable health risks. It would be wrong to assume

that all publications in this area are in complete agreement but we feel that these

three, thorough and expertly led studies should be taken as strong evidence against

any opposing claims.

2) Phone masts are unsightly

We certainly do agree that there are more visually appealing, man-made structures, however,

we feel this is a weak argument for a number of reasons.

Firstly, the unsightliness of a phone mast in the area is a small price to pay when considering a

cost-benefit analysis. Our data shows that there is a significant and severe daily impact for the

many users in the area that suffer poor network coverage. This impact cannot be said to just

affect casual users, and we must consider those who use their mobile phones for business

purposes and as a device of last resort in times of emergency. However, in all cases, the

unsightliness of a mast cannot be said to override the severity of poor signal coverage for the

majority.

Secondly, the benefit of wireless connectivity between masts and phones means that we may

choose where to locate the structure. We therefore have the ability to minimise its visual

impact by locating it somewhere where it is visually obscured, or ‘disguising’ the mast so as to

blend it in with its natural surroundings 21. This last point should encourage designers and the

Council to be given free rein in determining where the mast will be located and how it will

17 http://www.mthr.org.uk/documents/MTHR_report_2007.pdf 18 http://www.mthr.org.uk/documents/MTHRreport2012.pdf 19https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/333080/RCE-

20_Health_Effects_RF_Electromagnetic_fields.pdf 20 http://www.millionwomenstudy.org/introduction/ 21 Here is an article of some measures that have been taken around the world to improve the visual quality of phone masts:

http://techmash.co.uk/2012/08/20/why-do-some-people-think-mobile-phone-masts-are-ugly/

http://www.mthr.org.uk/documents/MTHR_report_2007.pdf

http://www.mthr.org.uk/documents/MTHRreport2012.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/333080/RCE-20_Health_Effects_RF_Electromagnetic_fields.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/333080/RCE-20_Health_Effects_RF_Electromagnetic_fields.pdf

http://www.millionwomenstudy.org/introduction/

http://techmash.co.uk/2012/08/20/why-do-some-people-think-mobile-phone-masts-are-ugly/



look. The product of such a negotiation will undoubtedly help to alleviate the visual impact

and with it any concerns that may have arisen.

3) Installation may be damaging to the environment

We feel strongly about environmental degradation and consciously oppose unnecessary or

mass destruction of it. However, the construction of a phone mast does not pose a significant

threat to the environment nor is it an unnecessary exercise as we will now explain.

The aforementioned reports, as well as The Environmental Health Trust’s rebuttal of an

opposing argument in 2013 22 has identified no environmental impact of mobile devices and

masts. We feel these reports provide a forceful argument on this matter that should be

considered by anyone with environmental concerns. In addition to this, environmentalists

must recognise that improved digital communications mean individuals require less travelling

to connect with others and carry out daily tasks. For example, if a business user in the Village

can now contact their clients more regularly by mobile (assuming the connection has been

improved), then they can avoid unnecessary transportation that would have otherwise

emitted certain pollutants.

In terms of importance, the installation of a phone mast will provide better coverage to the

many in the area who have stated that they cannot obtain a good network signal. It is for this

reason and the 98% (of our surveyed respondents) who stated their agreement that

something needed to be done, that installation cannot be considered an unnecessary

exercise.

4) There is nowhere to put the mast

We feel again that this excuse does not pose a significant threat to mast installation. Saughall

is geographically ideal for placement as it is high above seawater and is surrounded by a lot

of used and unused land. The distinction will be important with unused land much more

promising than the used land, but there will undoubtedly have to be discussion and

negotiation in both cases.

We understand that the central area of the village is built up with very little room, but in an

ideal situation the mast would be placed more towards the north of the village where the land

is much higher leading to better signal coverage.

The exact location of the mast would be a highly debated matter, which we think is a

desirable situation to ensure all concerns are addressed. However, to assume that there is no

place for the mast seems unfair to the location and should not be the deciding factor in

determining whether or not to have one.

We recommend users should be entitled discounted phone tariffs

Secondly, we recommend that users suffering from poor network coverage in the area should receive

discounted tariffs on their mobile contracts. This will of course depend on a number of factors as well

22 http://ehtrust.org/wp-content/uploads/2013/11/FCC.pdf

http://ehtrust.org/wp-content/uploads/2013/11/FCC.pdf



as whether or not the previous recommendation has been put into action. We have therefore left this

recommendation deliberately vague, as we feel a more profitable venture would be to negotiate on all

tariffs and all potential discounts.

What is not vague is the unacceptable current situation where users are paying for an unusable

service at premiums mirrored by those charged in other areas around the country with excellent signal

coverage. This is inadmissible, unfair and poor customer practices. The village and residents deserve

representation from larger bodies such as Ofcom (the telecommunication regulator), national and

local government, who have the responsibility of acting on behalf of citizens in places around the

country.

We are certain that such bodies can put forward a strong argument if it is positioned correctly. One

way this can be done is by recognising the mechanisms involved in free markets, whereby agreement

from a single provider may be all that is needed to catalyse a broader impact. If one provider agrees

to negotiate and alter terms to ensure Saughall residents are dealt with fairly, individuals would

gravitate towards this network which would stimulate other providers to acquiesce and make similar

concessions; this should eventually ensure a significantly comprehensive benefit for residents and

users in the Village. This report facilitates a powerful argument to support these potential negotiations

and may be drawn upon where necessary.

Second Best Solutions

We recommend boosters be provided for all networks in the area:

Booster technology is used by many networks 23 as a cheap and convenient alternative to mast

installation (or monetary concessions). Boosters are small devices or apps that enable the user to

connect via Wi-Fi (or through other means) which improves signal reception for devices in the

proximity. These are often provided free or at a small cost by the network providers (others are pricier

such as a one off cost of £69 for Vodaphone’s Sure Signal device).

Currently, not all households and users have access to booster technology and we would like to see all

networks with the ability to provide these things to do so. This should be done at small or subsidised

cost for users in the area, but ideally we would like to see this technology given to customers free of

charge. Networks should be asked formally to consider this, and where refused should be required to

give ample reasoning that demonstrates how they come to this decision while still ensuring they are

acting with customer’s best interests at heart.

While boosters do provide a suitable alternative to the aforementioned recommendations they are

many difficulties with them which make them a Second Best rather than First Best Solution. Booster

technology often uses Wi-Fi as a means of transmitting a more powerful signal. This is fine for users

with access to Wi-Fi, but for those who do not or who own old or outdated devices not equipped with

the necessary technology, this is not a suitable solution. Furthermore, other types of boosters only

tend to work if the device is used in the immediate proximity and only for those which are connected

up to the device. This condition seems almost paradoxical to what a mobile device should actually be

capable of: anywhere and anytime communication.

We recommend individuals be informed about the signal coverage in the area

as well as which phone network are best for the area

23 Tu Go (O2), InTouch (Three), Sure Signal (Vodaphone)



We would also expect those with the capacity to inform those living (or planning to live) in the area

about the severity of this issue as well as which networks are best for users and which they should

avoid entirely. In the case of our data, we would recommend Virgin and Vodaphone (but to also make

users aware that these are the best of a bad bunch and to not assume all users will be guaranteed

good coverage on these networks) and to definitely avoid Three and O2. We feel this must be done if

we are to act within the best interests of residents and users in the area as information provision is a

fairly inexpensive campaign on such a small level.

One last point to make about this recommendation is that it can potentially have a similar impact to

discounted tariffs (a First Best Solution). When individuals are aware which networks are the best, they

will transition towards those providers which catalyses other providers to improve their signal

coverage.

Third Best Solution

We recommend greater recognition that this issue affects all age groups

This is a very simple recommendation to act upon and the reasons for which should be clear to any

who has read this report. Our data has helped to disprove a common assumption that poor signal

coverage only impact certain age groups. We hope the readers of this report will recognise that poor

network coverage impacts all age groups. Ignorance towards this discovery does not help tackle the

issue at play and may in fact lead to an unnecessary regression.

2.5 Closing Remarks

We have now come to the end of this report and it is time for us to conclude with some closing

remarks.

We have covered two main areas of analysis: primarily, the signal coverage in Saughall and

secondarily, how certain network coverages impact different age ranges. The former has

demonstrated that poor network coverage spans across the entire area and to all network providers,

while the latter has shown that such coverage has an adverse effect on individuals from all age ranges.

These discoveries embody the urgency and frustration amongst the community that has been

somewhat neglected. The 98% of respondents who said that something needed to be done about the

signal coverage in Saughall illustrates a clear and overwhelming consensus for change. Based on this

and our other evidence, we have made some recommendations ordered in what we believe will have

the largest impact. Depending on which of these recommendations is enacted, it will have a certain

degree of alleviation. In any case what has to be recognised are the findings in this report; the first

step towards tackling this issue is to understand the problem and who it affects. Left dormant, this

issue will trouble anyone who plans to use a mobile device in the area, which is an undesirable

situation especially in an age where such devices adopt an increasing importance and purpose in our

daily lives.

It will be in the valiant hands of certain community members and councillors that this report will be

most effective; the discussion must be initiated at all levels and as many times as necessary to ensure

something is done. The work within this report and the many voices it speaks for represents an

unparalleled opportunity for action to be taken on this matter, it should not under any circumstances

be missed.



Lastly we would like to thank anyone who has taken the time to look at our work; it has been a great

pleasure constructing this paper and we hope that pleasure permeates through to the reader.

Limitations

We feel it is important that we mention and consider the limitations we experienced in this report that

did have an impact on our analysis. This section is important to the project but is not part of the main

report.

Time and resources

First and foremost, these two limitations were perhaps the most impactful to this study as they

affected all of its aspects. While this report has been completed thoroughly and with great care, it has

always been subject to time and resource constraints. With more of each we would have been able to

of obtained more responses, and perhaps from a greater area. We would have also had more ability to

analyse and present the data in a more forceful manner.

Absence of up-to-date records

Our report would have benefitted greatly from more up-to-date records on population estimates and

road names. The former would have enabled us to be more intricate about our population

calculations (and thus produce a more accurate sample size) and also of allowed more time for our

study, while the latter would have also saved us a great deal of time and improved our survey

distribution.

Creating a random survey

Secondly, we found it difficult to randomise our collection methods. Randomisation is important to

ensuring a fair and representative sample. As mentioned earlier, our intentions were to use a number

generator on the offline door-to-door surveying while allowing the online surveys (and offline static

survey) to be random by their very nature. Looking back at these measures it was very difficult to

ensure randomness across the board.

The offline door-to-door surveying number generator was not successful as we could not anticipate

whether anyone would be in the property at the time (this often had us going up and down roads

which proved laborious and time consuming). We instead opted for choosing houses which we

believed would have occupants present in the property (those with cars outside, lights on, etc.). While

it may be said that there is a large degree of chance associated with who is and is not in the house, it

was not as suitable as the random number generator. These methods would have to be revised if we

were to conduct the study again.

As for the offline static and online e-survey, we assumed them to be random simply in virtue of not

knowing who might fill them out. However, foresight is much easier than and hindsight and we found

our audiences were isolated to those with Facebook (for the online survey) and who were aware of the

events (for the static survey). This was not as random as we would hope as there was no chance that

anyone in the village without these means could have been aware or filled out the survey. Looking

and for future ventures, we should have provided information about the survey around the village and



set up other means by which it could be completed (such as a physical copy left in a certain location,

i.e. the Cooperative village shop).

Clarifications This section, while also not part of the main report, is important for any concerns that the reader may

have had while working through this paper. It takes some of the common questions which may have

arisen and gives our response.

Why was my road not covered?

Our survey area has been clearly defined meaning there are two possibilities if your road has not been

included: 1) your road is not within the survey area or 2) your road is within the survey area. In the

case of (1), your road was not included as we had limited our research to the location within the

boundaries that have been defined, and thus any areas outside would not have been considered in

this survey. In terms of (2) please ensure that your road was not included on our list and that it is

within the area and in Saughall. Assuming those last conditions are met, then we can only apologise if

a mistake has been made on our behalf. This will have no doubt been down to one of the

aforementioned limitations and should not be assumed to be of any significant reasoning.

Why was Q3 not included in the overall report?

Q3 was not included because of two reasons that have already been covered. Firstly, Q3 was

incompatible with Q2 as signal coverage rating is also a questions of signal consistency, i.e. there was

no need for Q2. Secondly, two of the answers provided in Q3 were virtually synonymous (‘Inconsistent’

and ‘Mixed’). We did still obtain the data for this question and have still included mention of it in the

report, but we felt the data it produced was open to many flaws compromising its significance.

How come you only asked 346 people?

We calculated an appropriate sample size for Saughall (see 1.4) based on the population of 3,386

(adjusted from the 2011 Census by the ONS), a confidence interval of 5%, a confidence level of 95%,

and a response distribution of 50%. We could have asked more people, which would have made the

results more accurate but as we reached the target at a point that was far beyond our allocated time

(see Time Frame below), we decided to simply move on to our analysis.

Why did you do this?

As members of the community we feel that there is a problem with the signal coverage in the

Saughall area. We feel we have a duty to other members to ensure their voices are heard on this

matter. Furthermore, we are social science students at the University of Manchester and Manchester

Metropolitan University meaning this type of study is of great interest to us.

Time Frame



This section again is not part of the main report but is designed to give the reader (who is interested)

an insight into what our project looked like in terms of time and stages.

We split the project up into four stages: Stage [1] was our preparation stage, Stage [2] the field

research, Stage [3] was about statistical analysis, and lastly Stage [4] is about finalising and distributing

the report.

We have included a time frame table in the Appendix, Figure 4, which shows the stages, our objectives

at each stage, the time we allocated for that stage followed by the expected and actual dates of

completion. We have also included a break in the report which is meant to represent a visit we made

to Cambodia during the project and to show that the project had to be put on hold for that duration.



Appendix

Figure [1] – Survey Form

1. What is your road name and number?

2. How would you rate the signal coverage for your mobile handset when using it within the

Saughall area? (N.B. this does not concern other devices such as a telephone, broadband etc.)

3. How consistent is the signal coverage for your mobile device within the Saughall area? Respondent 1 Respondent

2 Respondent 3 Respondent 4

Consistent Mixed Inconsistent Other (please write)

4. Who is the provider of your mobile device signal?

Respondent 1 Respondent 2


O2 EE Vodaphone Tesco Mobile Other (please write)

5. How old are you?

Respondent 1 Respondent 2 Respondent 3 Respondent 4 <16 16-24 25-45 46-65 66+

6. How would you rate the impact of the mobile signal service on your day to day life?





Very Poor Poor Mixed Good Very Good

Respondent 1 Respondent 2 Respondent 3

Respondent 4



7. Do you have a landline?

8. Broadly speaking, do you think something should be done about the mobile phone signal coverage in the Saughall area?

Figure [2] – Survey Area

Very problematic

Problematic Little affect No affect whatsoever Enhances daily life


Respondent 4

Yes

No Other


Respondent 4

Yes

No Other



(Google Maps, 2016)

Figure [3] – Road Names

1. Aldersey Close

2. Anvil Close

3. Aspen Grove

4. Chapel Close

5. Church Road

6. Church Road

7. Coalpit Lane

8. Crofters Way

9. Darlington Crescent

10. Eastfield’s Grove

11. Fairholme Close

12. Fernlea Court

13. Fiddlers Lane

14. Fieldway

15. Fox Lea

16. Green Lane

17. Greenway

18. Haymakers Way

19. Hermitage Court



20. Humphrey Close

21. Kingston Court

22. Kingswood Avenue

23. Kingswood Lane

24. Larchfields

25. Lodge Lane

26. Long Lane

27. Maplewood Grove

28. Meadowcroft

29. Meadows Lane

30. Newcroft

31. Park Avenue

32. Park Way

33. Parkgate Road

34. Rake Way

35. Rosewood Grove

36. Saughall Hey

37. Seahill Road

38. Smithy Close

39. The Close

40. The Ridings

41. Thomas Wedge Road

42. Thornberry Close

43. Timberfields Road

44. Vernon Close

45. Vernon Institute

46. Whaley Court

47. Willow Hey

48. Worsley Avenue

49. Yew Tree Avenue

Figure [4] – Time Schedule

Stage Objectives Time Allocated Deadline Date of

completion

Project

commences

11/07/2016



Stage [1]

Preparation

Establish what we

are analyzing

Design and print

questionnaires

Determine what

and who we are

measuring

Establish a

sample size

Work out how we

will carry our

analysis

Determine a

sample

randomising

method

Two Weeks:

We were quite

generous with time

allocation on this

stage as we felt

preparation and

preliminary research

was vital to the

success of the project.

A clearly defined area,

a suitable

questionnaire and the

methodology behind

our sampling would

mean the difference

between a project

that produced any

statistically significant

results and one that

did not.

24/07/2016 22/07/2016

We felt

comfortable by

this date to say

our preparation

stage was

complete under

our deadline

time.

BREAK FOR

CAMBODIA

Stage [2]

Conducting

field research

Gathering data

using sample size

and sample

methods

Posting the

online survey

through different

channels

Spreading

general

awareness about

the survey

One week:

This is quite an

ambitious time

allocation but with

adequate planning

from Stage [1] and

our determination we

feel we can achieve

this result.

29/08/2016

07/09/16

We ran

considerably

over our

estimated time

as we did not

anticipate how

long data

collection would

take.

Stage [3]

Conducting

statistical

analysis

Record the data.

Conduct analysis

on the data

looking for results

the fit or do not

fit our

hypotheses.

One week:

Recording the data

from our field

research will take

quite some time to

complete. We then

14/09/16 14/09/2016

This section was

completed in the

allocated time

and by the date



Make

recommendations

based on this

data

must leave enough

time to engage with

the bulk of our project

and conduct our

statistical analysis.

This will be followed

up by our

recommendations

of expected

completion.

Stage [4]

Finalising

and

distributing

report

Present the data

in reader friendly

ways (charts,

diagrams

distribution,

graphs etc.).

Complete

summary sections

(General and

findings) as well

as our

conclusions.

Distribute report

to relevant bodies

One Week (ongoing

for distribution):

The finalising section

could have been

allocated less time but

we wanted to allow

for any potential

issues that might

come in data analysis.

21/09/2016 26/09/2016

We failed to

meet our

expected target

and began

distributing 5

days after

expectations.

This was down to

some issues that

came up in our

finalising stage.

Once we had

completed the

report we felt

one of the

methods used to

analyse the data

was not as

suitable as an

alternative. This

meant changing

and reorganising

an entire section

which then

changed a lot of

the remaining

report. Despite a

generous time

allocation, we did

not anticipate

coming into an

issue as large as

this.

Project

finishes

26/09/2016



Bibliography

Google Maps. (2016). Map of Saughall Area. Retrieved from

https://www.google.co.uk/maps/place/Saughall,+Chester/@53.2276614,-

2.9866055,13z/data=!3m1!4b1!4m5!3m4!1s0x487adc5e2bc4869d:0x961f69099b688b8d!8m2!

3d53.2233329!4d-2.959321 Office for National Statistics . (2011). Saughall - Key Figures for 2011 Census. Retrieved from Office for

National Statistics - Neighbourhood Statistics:

http://www.neighbourhood.statistics.gov.uk/dissemination/LeadKeyFigures.do?a=7&b=11128

209&c=CH1+6BE&d=16&e=62&g=6407207&i=1001x1003x1032x1004&m=0&r=0&s=14680

94879188&enc=1&nsjs=true&nsck=false&nssvg=false&nswid=1206 Office for National Statistics . (2016, June 23). England population mid-year estimate. (E. Shrosbree,

Editor) Retrieved from Office for National Statistics:



https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populatio

nestimates/timeseries/enpop/pop

If you have any questions about this report please contact us at [email protected]

http://[email protected]

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