Questionnaires distribution and sorting

In response to the difficulties that have been encountered during the piloting phase in terms of the distribution of the questionnaires, an alternative strategy was applied to attain wider distribution of the questionnaires and guarantee higher response from households. For this alternative strategy, ten out of the 18 identified urban districts, representing the five different social classes, were initially selected. Each social class was represented by two districts. Ten assistants, each of whom lives in one of the selected districts, were assigned to carry out the survey and distribute the questionnaires among local households. Each of the assistants was responsible for distributing the questionnaires in different geographical locations within the district in which they live, so that it would be easier for them to work within areas that they are familiar with - the factor that might help getting more friendly responses from local households who live in the same district. Each assistant was clearly informed about the study and the questionnaire used for the survey, so as to be able to answer any raised questions or queries from the survey respondents.

To reach a higher number of households, within the limited time frame of the survey, questionnaires were distributed either directly to houses or in local public venues, comprising in particular, shopping facilities and mosques, in addition to some working places. Note that in order to approach working places it was necessary to contact an employee working there in order to make all necessary arrangements. Regarding the first approach, i.e. distribution to houses, questionnaires were distributed among neighbours and people known by the assistant who in turn distributed further number of questionnaires among their neighbours or people they know who live in the same

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district. This made it possible to gain higher degree of response and accordingly bigger number of questionnaires in a shorter period of time. Regarding the public venues, questionnaires were distributed randomly among people who were willing to participate. Questionnaires were either filled in presence of the research assistant, or filled later and collected afterwards by the assistant. Figure 4.7 illustrates the applied sampling and questionnaire distribution strategy.

The aim was to achieve a total number of one thousand completed questionnaires with a minimum number of eighty questionnaires for each district in order for the district to be statistically representative. Nearly 1550 questionnaires were distributed all over the ten districts. Respondents were asked to state the basic information related to their place of living including the name of the district, neighbourhood and street and the number of the property in order to provide a coding guidance for the researcher. Out of the 1550 distributed questionnaires, 980 questionnaires were returned. These were assessed according to specified criteria that included the exclusion of any faulty, incomplete or incorrectly filled-in questionnaires, and questionnaires from districts that are not included in the research sampling frame⁴. The remaining applicable questionnaires were then sorted according to the districts and neighbourhoods to which they refer. In respect of that, two districts achieved a total number of questionnaires that are far below the targeted number which is a minimum of eighty questionnaires for each district. These were accordingly taken away from the study and their questionnaires were set aside.

Note that achieving a reasonable or statistically sufficient number of respondents was not possible on the neighbourhood scale and, thus, the district scale was adopted for the analysis.

4 As a result of distributing questionnaires in public venues, i.e. shopping facilities and mosques, as well as in working areas, some questionnaires were filled by people who were present in those places but live in districts other than the ones in which they were given the questionnaires. Such questionnaires were sorted out and placed within the districts to which they belong, in case these districts were included in the study; otherwise they were taken out from the final set of accepted questionnaires.

Page | 131 Figure 4.7: Questionnaires distribution strategy

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Out of the 980 returned questionnaires 205, were rejected because of not being qualified. Reasons for disqualification included: being incomplete, some significant questions not being answered and lack of seriousness in filling the questionnaire. The latest point was noticed from reviewing the whole questionnaire and finding some contradictions in the answers that did not make sense. Other reasons for rejecting questionnaires included the loss of one or more of the preconditions related to the person eligible for filling out the questionnaire. For example, some questionnaires were found to be filled out by individuals who are less than 18 years old, contrary to the requirement of being 18 years or above to take part in the study. The final overall sample size of 775 households was achieved. These were split over eight districts with an average of 97 households in each. Figure 4.8 illustrates the filtering procedure used in determining the final set of accepted questionnaires, while Tables 4.5 and 4.6 provide a breakdown of the sample according to districts and socio-demographic attributes of respondents and according to housing provision characteristics respectively.

Figure 4.8: Questionnaires filtering procedure

Page | 133 Table 4.5: Frequencies of districts and socio-demographic characteristics of the study sample

Variable Categories Frequency Valid Per cent

District Telaa AlAli, … 101 13.0%

Level of Education Primary education 39 5.1%

Secondary education 144 18.7%

College or diploma 133 17.2%

University degree 332 43.0%

Higher education 124 16.1%

Total 772 (missing = 3)

Employment Self employer 97 12.6%

Employed (public sector) 206 26.8%

Employed (private sector) 323 41.9%

Un employed 93 12.1%

Other 51 6.6%

Total 770 (missing = 5)

Household Structure Single 18 2.3%

Couple 53 6.9%

Page | 134 Table 4.6: Frequencies of housing provision characteristics of the study sample

Variable Categories Frequency Valid Percent

Tenure Type Own outright 322 41.7% quantitative data. Different statistical tests and procedures were applied in respect to the type of analysed data. These include descriptive univariate analysis comprising frequencies and measures of central tendency, i.e. mean, median and mode, and descriptive bivariate analysis including cross tabulations, correlations, means comparisons and others. Different types of graphs and diagrams including box plots, scatter plots and bar charts were also used for investigation and illustration. Table 4.7 presents all statistical analytical procedures, tests and graphs used for data analysis in relation to the type of data being analysed. Non-parametric standard tests were used assuming data do not follow a normal distribution.

Note that due to the variations in the types of collected data (numerical and categorical) it was necessary to carry out statistical analysis that fit with each type. This, however, made it not possible to investigate the relationship between all measures. Taking into consideration that the majority of collected data were in the form of categorical data, transformation of numerical data was needed. Therefore, all numerical data were re-coded from their original form into ordinal forms of five categories in most cases. Such data included socio-demographic factors and housing provision factors such as age, number of people living in the house, number of dependent children and length of