COVENTRY UNIVERSITY
27
SCHOOL OF BUSINESS ANDENVIRONMENT
102 – STATISTICALANALYSIS FOR ACCOUNTING AND FINANCE
ASSIGNMENT – 201315
ASSIGNMENT TITLE: SURVEYANALYSIS
Tableof Contents
Executive Summary 3
1.0. Introduction 4
1.1. Aims and Objectives of the Survey 4
1.2. Hypothesis of the study 5
2.0. Background To SIES 6
2.1. Establishment and Objectives of SIES 6
2.2. Major changes to Student Finance 7
2.3. Source of Student Finance 7
3.0. Sampling 8
4.0. Data Collection 9
4.0. Results 9
4.1. Descriptive Analysis 9
4.1.1. Summary of Family Situation 9
4.1.2. Trends in Total Yearly Living Costs 10
4.1.3. Domicile Rates 12
4.1.4. Scatter and Historical 14
4.1.5 Distribution of Total Income 15
4.1.6 Distribution of Total Expenditure (Q and D) 17
4.2. Hypotheses Testing 18
4.2.1. Hypothesis 1 18
4.2.2. Hypothesis 2 19
4.2.3. Hypothesis 3 20
Conclusion 21
References 23
ExecutiveSummary
The commissioning of the2007/08 Student Income and Expenditure Survey (SIES) by Welshgovernment and Department of Business Innovation and Skills (BIS) wascritical to providing comprehensive information regarding thespending and income situations amongst the students in UK.
The current paper investigatesthe SIES in UK and the factors affecting the student fraternity ininstitutions of higher learning in areas of income generation and therelated expenditure. Various factors have been investigated such asthe family and support to students, the full time, and part timeprograms based on domicile country, the income, expenditure andrelated correlation between the two. It was determined that parentshave been instrumental in supporting their children. This wasbackedup by the information regarding the income and expenditurecorrelation where most students seemed to spend much more than theirincomes. Hence, a reflection that parents provided any otheradditional support to students. The average annual values for livingcosts, income, and expenditure, are £6000, £11,000 and £12,000respectively.
Two out of the threehypotheses formulated in the current paper were fulfilled while theone null hypothesis was fulfilled. According to the hypotheses tests,parents play a major role in supporting their children ininstitutions of higher learning, many students are on fulltimeprogram, and that many students are not financially independent.
1.0.INTRODUCTION
In the recent past, manystudents have been taking the initiative of joining institutions ofhigher learning by themselves. Therefore, the students require tocontrol their mode of spending money sustainably. To facilitateacquisition of the information regarding students` income andexpenditure, the Student Income and Expenditure Survey (SIES) havebeen instrumental in providing detailed and uptodate assessment,taking into consideration the changes taking place in students`funding and any other financial support. The target population forthe study was full the time and part time students in HigherEducation Institutions (HEI) and the Further Education Colleges(FEC), inclusive of Open University (OU).
The sample targeted theundergraduate students undertaking their first degree, higher diplomaof certificates, as well as postgraduate universitybased trainingcourses. The 20072008 survey is the most recent among the series ofSIES surveys carried at 3year intervals. Therefore, the currentpaper, a survey analysis of the income and expenditure amongst thestudents has been carried out, and the results presented in thispaper. The major sources of income will be evaluated and described,and the major expenditure avenues examined. The major sectionscovered include market background that evaluates the size, social andethnic status of the student population in UK, sampling and relatedissues in getting the most appropriate representative sample due tolarge students` population in UK, descriptive statistics of theresults, hypotheses tests and conclusions based on the results.
 Aims and Objectives of the Survey
Below are the objectives ofthe current paper

Do determine the rate of dependence on students

To evaluate the distribution of total annual living costs among the students

To calculate the domicile rates for Welsh and English students

To find out the correlation between income and expenditure among the students

To analyze the distribution of annual income and expenditure among the students
 Hypothesis of the study
A hypothesis is an exclusiveprediction of a statement, and it provides a detailed concretedescription of terms that are expected to happen in a study.Therefore, a hypothesis has a prediction or alternative hypothesessuch as H1 or HA, and the null hypothesis, HO or H0. The currentstudy aimed at determining the correlation between students’expenditure, income and their source of funds. The three hypothesesare as follows
H1:Most students are financially independent in terms of their careerand education
HO_{1}:Most students are not financially independent in terms of theircareer and education
H2:Most students get funds from their parents
HO_{2}:Most of the students do not get funding from their parents
H3:Many students England and Wales are in a fulltime program, and theywork to pay for their fees
HO_{3}:Many students England and Wales are in the parttime program and donot they work to pay for their fees
2.0.BACKGROUND TO sies2.1.Establishment and Objectives of SIES
The SIES was designed withthe intention of providing detailed information regarding the incomeand expenditure amongst the students in United Kingdom. The SIESpresents an objective and authoritative report pertaining thecircumstances of students` education in UK. The survey involves theuse of a representative sample of the eligible students. The datacollected covers the debt, income, expenditure and any experience offinancial hardship[ CITATION Cal01 l 1033 ].Also, SIES examines how the experience of the students in highereducation is affected by finances. The information from the surveysis used as evidence through which student support system policies areformulated.
The SIES have regularly beenconducted in line with the government requirement since 1980s thoughthis has changed recently as the studies are conducted in theintervals of three to four years hence the latest survey wasconducted in 20072008. This survey used a sample of approximately3,500 fulltime and parttime students within the higher education.The surveys involved facetoface interviews, as well as expenditurediaries. The survey has traditionally relied solely on randomprobability sampling, hence issues with breach of students`confidentiality and data protection, especially during the periodsbetween 1980s to late 1990s[ CITATION Fin06 l 1033 ].However, the most recent surveys have adopted quota and randomsampling that has enhanced data protection and confidentiality.
Overtime, the SIES, just likeany other survey, has suffered from the reduction in response rates.As results, plans are underway for review of sampling methodology andstrategy. The 20072008 survey recommended continued use of theprobability sampling over facetoface interviews and quotasampling[ CITATION Low09 l 1033 ].
2.2.Major changes to Student Finance
Many changes in the waystudents fund their higher education have taken place. Amongst themost significant is the shift in public funding system to studentloans from student grants, as well as an introduction of tuition fee.Other changes include the repayment of loans, and financial helpaccorded to some students[ CITATION Har12 l 1033 ].
Since the 1980s devolution inUK, various countries have introduced different funding systems forstudents. Also, Acts have been enacted on tuition regime and studentsupport. This reflects the various trends in the past one decade onhow the students have been financing their studies to supplementloans and grants. For instance earnings have become significantsource of income amongst many fulltime students, have enhancedgrowth for parttime students, and have resulted in many studentsgoing leaving education due to lack of earnings[ CITATION Cal01 l 1033 ].
2.3.Source of Student Finance
The undergraduate students inUK have, since 1998, been contributing their tuition £1,000annually, after which it rose to £1,150 from 2004. This was mostlydependent on the ability of the parent or guardian. The threshold ofparental contribution has been increased since 1998 to exclude manystudents from contributing in payment of their fees[ CITATION Cal01 l 1033 ].Also, since 1998, the maintenance grants were phased out forstudents, and student loans become the major form of funding forfulltime students. This also saw the changes in repayment systemfrom mortgage style toincome contingent mode that was linked to the income of the studentafter graduation. However, since 1999, the student loans havesubstantially improved, with bursaries for disadvantaged studentsbeing introduced since 2000s[ CITATION Low09 l 1033 ].Also, the parttime students on low income have been able to accessfinancial help through loans, student support and remission fees.
3.0.Sampling
Sampling is the process oftaking a part of a large population to act as a representative fromwhich the inferences are drawn. The current study used the twostagestratified and random sampling methods. The first stage entailedselection of institutions of higher learning. The second stageentailed getting random samples of participant students andrequesting for their consent through sending to them forms to filland send them back. A sample of students was chosen from those whofilled and returned the forms. Out of the all the students contacted,only 3,430 were chosen to participate in the survey.
One major drawback in choosingthe sample was the difficulttoreach students, especially those whowere in parttime programs. This implied vulnerability of bias tofulltime students as opposed to taking a representative sample thatcloser to if not 5050 percent basis. Zhang and Mingfang (2014)noted that random may be misleading in representation of the overallpopulation. Their argued that this is particularly disadvantageouswhere the area of study is large. Hence, the current research may bevulnerable to these challenges since it covers extensive studentpopulation across UK.
4.0.Data Collection
Data was collected throughfacetoface interviews supplemented by 14day spending diary thatprovided estimates for the selected expenditure items. This was doneon papers and collected by the interviewer. The participant studentswere also given the option of filling their spending diary online.This was followed by the extensive survey of family resources.
4.0.Results4.1.Descriptive Analysis
SPSS was used to conduct theanalysis. The sample comprised of 3430 students. In this paper, bothqualitative and quantitative data was used in the analysis and theresults presented in the graphs below.
4.1.1.Summary of Family Situation
The analysis of familysituation sought to determine whether a student was living with thefamily parents during term time.
Table 4.1:Family Situation
If lives with parents during termtime 

Yes 
No 

Count 
Count 

Family situation summary 
1 
4 
454 
2 
7 
190 

3 
20 
425 

4 
680 
1650 
It can be seen from the Table4.1 that the number of students living with their parents varied,where the SPSS value 1 had 458 students, 4 lived with their parentsand 454 do not live with their parents, 2 had 197 students, 7 livedwith their parent while 190 did not, 3 had 445 20 lived with theirparents while 425 did not and 4 had 2330, 680 lived with theirparents while 1650 did not students.
Figure 4.1: FamilySituation
The figure 4.1 shows that thegreatest number of students were living with independently free oftheir parents.
4.1.2.Trends in Total Yearly Living Costs
Theresponses to trends yearly living costs were analyzed and frequencydistribution chart showing the distribution ranges is presented inFigure 2 below.
Figure 4.2: FrequencyDistribution Graph for Estimated Yearly Living Costs
It can be observed from Figure2 that more than half of the students have their annual expenditurebelow 6000. Also, it can be deduced that averagely, the total livingcosts for each student is £6620.17. From the value of standarddeviation, £5773.65, we can conclude that the greatest percentage ofthe students fall between £5773.65 less the mean and £5773.65 afterthe mean, which is between £1046.52 and £12293.82.
Table 2 below presents thedescriptive statistics obtained
Table4.2:Descriptive Statistics
Range 
Frequency 
Descriptive Statistics 

0 
332 
Mean 
6620.175121 

2000 
291 
Standard Error 
98.58336081 

4000 
554 
Median 
5538.06 

6000 
678 
Mode 
0 

8000 
527 
Standard Deviation 
5773.653009 

10000 
370 
Sample Variance 
33335069.07 

12000 
237 
Kurtosis 
14.8691058 

14000 
146 
Skewness 
2.482153698 

16000 
99 
Range 
76919 

18000 
60 
Minimum 
0 

20000 
36 
Maximum 
76919 

22000 
27 
Sum 
22707200.66 

24000 
18 
Count 
3430 

26000 
14 

28000 
9 

30000 
11 

32000 
2 

34000 
6 

36000 
5 

38000 
2 

40000 
1 

42000 
1 

>42000 
3 
It can be seen that the 332students out of the 3430 respondents have their annual expenditureless than £2000, 291 students have their annual expenditure between£2,000 and £4,000, 554 students spend between £4,000 and £6,000,678 between £6000 and £8,000, 527 between £8,000 and £10,000, 37between £10,000 and £12,000, 237 between £22,000 and £14,000, 146between £14,000 and £16000, 99 between £16,000 and £18,000, 60between £18,000 and £20,000, 36 between £20,000 and £22,000, 27between £22,000 and £24,000, 18 between £24000 and £26,000, 14between £26,000 and £28,000, and the rest, 40students have theiryearly expenditure more than £28,000.
The highest spender amongstthe students spends approximately well above £70,000. From the 3430student sample, 332 cannot account for their spending. This impliesthat there must be someone who provides for their expenses.
4.1.3.Domicile Rates
The study covered bothparttime and fulltime Welsh and Englishdomiciled students. Theresults are presented in figure 4.3 below.
Figure 4.3: PartTime and Full TimeRates for English and Welsh Domiciled Students
It can be observed that thehighest number of students, 59.62 percent are English Domiciled andare on fulltime program. This is followed by EnglishDomiciledparttime students at 18.69 percent. The Welshdomiciled students ona fulltime program are 16.03 percent while those on the parttimeprogram are 5.66 percent.
4.1.4.Scatter and Historical
The regression analysis forincome versus expenditure was sought, and the results are presentedin figure 4.4 below
Figure 4.4:Regression of total income versus estimated total annual expenditure
It can be seen the correlationcoefficient, R^{2}is 0.1471, which is considerably lower than one. This implies thatthe income for the students and expenditure cannot be correlated. Thegraph exhibits substantial scatter and this is indicative ofmismanagement of finances or many students are funded from sourcesother than their income.
4.1.5Distribution of Total Income
Table 4.5:Frequency Distribution of Total Income and Total Expenditure
Range 
Frequency (Income) 
Expenditure Frequency 
0 
4 
0 
2000 
41 
24 
4000 
119 
126 
6000 
290 
289 
8000 
536 
441 
10000 
673 
545 
12000 
550 
528 
14000 
406 
403 
16000 
269 
289 
18000 
198 
211 
20000 
113 
155 
22000 
78 
127 
24000 
42 
72 
26000 
28 
48 
28000 
21 
54 
30000 
22 
29 
32000 
12 
31 
34000 
3 
10 
36000 
3 
8 
38000 
7 
11 
40000 
5 
6 
42000 
3 
4 
44000 
3 
4 
46000 
1 
3 
48000 
0 
4 
50000 
0 
3 
52000 
1 
0 
54000 
1 
0 
56000 
1 
0 
58000 
0 
1 
60000 
0 
1 
62000 
0 
0 
64000 
0 
0 
66000 
0 
1 
68000 
0 
0 
It can be noted from Table 4.5above that most spenders are not necessary under income. The expensesappear to be higher than the income. The figures 4.5 and 4.6 belowpresents the frequency distribution of total income and totalexpenditure.
Figure 4.5:Income distribution
The average income of perstudent is £11,237.87 while the standard deviation is £5,741.23.FromFigure 4.5, very few students have an income of more than £30,000.
4.1.6Distribution of Total Expenditure (Q and D)
The figure 4.6 below presentsthe distribution of total expenditure.
Figure 4.6:Distribution of Total Expenditure
From Figure 4.6, each studentspends an average of £12,529.88, and the standard deviation is£7090.19. When compared to the income distribution, we can concludethat averagely, students spends much more than they generate.
 Hypotheses Testing
TheChisquare tests and cross tabulation tables were used in theanalysis to test the hypotheses.
Firsthypothesis
 Hypothesis 1
SocioEconomic Class * Student Status Cross tabulation 

Student Status 
Total 

Dependent 
Independent 

SocioEconomic Class 
Managerial or Professional 
Count 
970 
641 
1611 
Expected Count 
825.0 
786.0 
1611.0 

Intermediate 
Count 
284 
303 
587 

Expected Count 
300.6 
286.4 
587.0 

Routine and Manual + Unemployed 
Count 
307 
479 
786 

Expected Count 
402.5 
383.5 
786.0 

No paid work prior to course 
Count 
91 
151 
242 

Expected Count 
123.9 
118.1 
242.0 

Total 
Count 
1652 
1574 
3226 

Expected Count 
1652.0 
1574.0 
3226.0 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 

Pearson ChiSquare 
118.502^{a} 
3 
.000 
Likelihood Ratio 
119.370 
3 
.000 
LinearbyLinear Association 
22.256 
1 
.000 
N of Valid Cases 
3226 

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 118.07. 
Directional Measures 

Value 
Asymp. Std. Error 
Approx. T^{b} 
Approx. Sig. 

Nominal by Nominal 
Uncertainty Coefficient 
Symmetric 
.020 
.004 
5.520 
.000^{c} 
SocioEconomic Class Dependent 
.015 
.003 
5.520 
.000^{c} 

Student Status Dependent 
.027 
.005 
5.520 
.000^{c} 

a. Not assuming the null hypothesis. 

b. Using the asymptotic standard error assuming the null hypothesis. 

c. Likelihood ratio chisquare probability. 
From thecrosstabulation and chisquare test carried out, 0 cells haveexpected count of less than 5%. This is far much less than the 20%that is the minimum required significance.
Therefore,the most students are financially dependent on loans and grantsamongst others.This fulfills the first hypothesis that hypothesized that manystudents are dependent financially to fund their education.
 Hypothesis 2
The secondhypothesis aimed at determining whether most of the students get thefunding from their parents. The Chisquare tests and thecrosstabulation results are presented below
Family situation summary * If lives with parents during term time Cross tabulation 

If lives with parents during term time 
Total 

Yes 
No 

Family situation summary 
1 
Count 
4 
454 
458 

Expected Count 
94.9 
363.1 
458.0 

2 
Count 
7 
190 
197 

Expected Count 
40.8 
156.2 
197.0 

3 
Count 
20 
425 
445 

Expected Count 
92.2 
352.8 
445.0 

4 
Count 
680 
1650 
2330 

Expected Count 
483.0 
1847.0 
2330.0 

Total 
Count 
711 
2719 
3430 

Expected Count 
711.0 
2719.0 
3430.0 
Symmetric Measures 

Value 
Approx. Sig. 

Nominal by Nominal 
Phi 
.304 
.000 
Cramer`s V 
.304 
.000 

N of Valid Cases 
3430 

a. Not assuming the null hypothesis. 

b. Using the asymptotic standard error assuming the null hypothesis. 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 

Pearson ChiSquare 
318.009^{a} 
3 
.000 
Likelihood Ratio 
417.717 
3 
.000 
LinearbyLinear Association 
263.895 
1 
.000 
N of Valid Cases 
3430 

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 40.84. 
Thechisquare test results showed that a significant relationship existsbetween the family situation and the rate at which students spendwith their parents during the course of the term. Therefore,the 2^{nd}hypothesis is fulfilled most of the students get funds from theirparents.
 Hypothesis 3
Thissought to determine that education program taken by the students fromEngland and Wales. The results and chisquare tests are as presentedbelow.
Is your course Full time or Part time? * FT/PT by domicile Cross tabulation 

FT/PT by domicile 
Total 

EDFT 
EDPT 
WDFT 
EDPT 

Is your course Full time or Part time? 
Fulltime 
Count 
2007 
0 
513 
0 
2520 

Expected Count 
1543.9 
416.7 
415.2 
144.2 
2520.0 

Part time 
Count 
38 
552 
37 
191 
818 

Expected Count 
501.1 
135.3 
134.8 
46.8 
818.0 

Total 
Count 
2045 
552 
550 
191 
3338 

Expected Count 
2045.0 
552.0 
550.0 
191.0 
3338.0 

ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 

Pearson ChiSquare 
2949.874^{a} 
3 
.000 

Likelihood Ratio 
3068.087 
3 
.000 

LinearbyLinear Association 
772.939 
1 
.000 

N of Valid Cases 
3338 

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 46.81. 
The aboveresults show that most students are in a fulltime program, withEngland having more students than Wales. The chisquare tests showsthat a significant relationship exists between the domicile countryand the kind of the program undertaken by the student, eitherfulltime or parttime., hence fulfilling the third objective.
Conclusion
The current study aimed atidentifying the financial position in terms of expenditure and incomefor the students is institutions of higher learning in UK. The targetpopulation was the students from higher learning institution. Gettingan effective representative sample was, therefore, a major concerndue to the large population of the students in UK. As a result,random and stratified sampling methods were used in getting arepresentative sample. The data was collected through facetofaceinterviews.
The three major hypotheses ofthe study sought for the financial independence of students,relationship between family situation and the assistance from theparents, and the fulltime and parttime for the English andWelshdomiciled students.
In the data analysis, SPSSsoftware was used and the study sample comprised of 3430 students.Based on the family situation, most of the students do not live withtheir parents during term time. This implies that many students areindependent financially. It was determined that on average, theannual living cost for a student is approximately £6,000 income is£11,000 and expenditure are £12,000. These imply that studentsspend more than they can get from their incomes.
As such, other sources offunding should be provided, such as loans and grants, to support themfinancially. Finally, from the hypotheses testing, hypothesis 1 and 3were fulfilled, while null hypothesis 2 was fulfilled. Therefore, itcan be concluded that parents contribute significantly in terms offinances to the studies of their children in higher learninginstitutions, many students are financially dependent and onfulltime programs, hence need for more funding for loans and grants.
The results of this paper are,therefore, critical to the establishment of support programs andfunding policies to the students within the higher institutions oflearning.
References
Callender, C., & Martin, K. (2001). Students in Wales: An Analysis of Data from the Student Income and Expenditure Survey 1998/99. Cardiff: Independent Investigation Group on Student Hardship and Funding in Wales.
Finch, S. (2006). Student Income and Expenditure Survey 2004/05: Technical Report. London: National Centre for Social Research.
Harper, J. R. (2012). Student Income And Expenditure In The Universities Of Glasgow And Birmingham: A Comparative Survey. Scottish Journal of Political Economy 4(3), pp. 194206.
Low, N. (2009). Student Income and Expenditure Survey 2007/08. UK: National Centre for Social Research.
Zhang, H., & Mingfang, L. (2014). RWOSampling: A Random Walk Oversampling Approach to Imbalanced Data Classification. Information Fusion, pp. 1220.