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investigation on which several other types of studies can be carried out. The current study is an exploratory research due to the scarcity of data on economic activities in the slums of Ghana.
5.2.1.2 Descriptive Research
Descriptive statistics entails categorizing data through the presentation of figures. No assumptions are made in descriptive statistics since the goal is just to describe and summarise a set of data (Newbold, Carlson and Thorne, 2010). Descriptive research is used to describe variables rather than testing a predicted relationship between variables, providing simple summaries about a sample. Leedy and Ormrod, (2014, p. 190) refer to descriptive research as the identification of the features of an observed occurrence and examining an event “as it is”.
5.2.1.3 Causal Research
Causal research investigates whether or not a variable causes another to change; that is, does event A cause event B to change? Hence, the causal relationship between two or more variables are studied to learn about the causes of the change. Causality refers to the situation where a variable changes (the effect) due to the incidence of another variable (the cause). Causal research therefore seeks to establish the impact certain variables have on others. That is, whether a variable being removed or changed, will cause a variation in another variable (Sekaran and Bougie 2013, p. 98).
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This study uses mainly, primary data. This is due to the fact that, there is insufficient secondary data to help answer the study’s research questions. The Ghana Statistical Service does not provide information on the number of people operating in slum activities in the two slums under study.
5.3.2 Secondary Data
Secondary data is used to supplement primary data. Secondary data is data collected by some other researcher for another purpose (Boslaugh 2007, p. 1). Since informal sector activities in slums are a global phenomenon, secondary data from slums in countries such as Brazil, India, Kenya, Bangladesh and elsewhere will be incorporated into the current study. This will enable the researcher to identify whether the problems and challenges faced by slum operators within the informal sector in Ghana are similar to, or different from, those of other countries, and what lessons may be drawn from these for policy suggestions in Ghana.
5.3.3 Target Population
Levin and Fox (2011, p. 118) define a population as a group, entities that are linked together by at least one characteristic. This characteristic can be in terms of nationality, age group, race, gender, or residential areas. The population of the current study consists of operators engaged in informal sector activities in the slums of S&G in Accra and AL in Kumasi.
Data was gathered by means of questionnaires administered to the operators engaged in slum economic activities. There is currently no data on the actual number of people involved in informal activities in the slums of Ghana. Furthermore, the researcher cannot study the whole population, hence a sample was the target.
5.3.4 Sampling
A sample refers to a small number of entities drawn from a population with the appropriate method.
This gives researchers the opportunity to make inductive references about the population (Levin and Fox 2011, p. 118).
83 Table 5.1 Sampling methods and statistical strength
SAMPLING METHOD STATISTICAL STRENGTH
Probability
Simple Random High
Systematic High/Medium
Stratified High
Cluster Medium
Non-Probability
Quota Medium
Convenience Low
Judgement Low
Snowball Low
Respondent-driven Medium
Source: Dahlberg and McCaig (2010, p. 178)
Table 5.1 shows the different sampling approaches available to a researcher. The probability sampling methods are based on statistical theory and the non-probability sampling methods are samples that a researcher chooses based on his/her subjective judgement, in exploring the research questions. Samples obtained by the probability sampling are therefore highly representative of the population (Matthews and Ross, 2010; Dahlberg and McCaig 2010, p. 178). The current study employs the stratified random sampling technique. According to Dahlberg and McCaig (2010), the stratified random sampling method has a high statistical strength in terms of consistency with its predictive accuracy. Hence with probability sampling methods, researchers can make accurate measurements with the data (Yeager et al., 2011, p. 737).
5.3.5 Sampling technique
Stratified random sampling is a probability sampling technique, which enables sampling of populations that are divided into subgroups. This helps in obtaining a sample that is representative of all the subgroups, as each subgroup is subjected to a simple random sampling (Groves et al., 2009, p. 113; Newbold, Carlson and Thorne, 2010, p. 771). Such subgroups are referred to as
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‘strata’ (stratum; plural) and are mutually exclusive. Stratification divides a population into characteristic specific groups, for instance, divisions pertaining to geographical location, income bracket, and size of city (Deming 1966, p. 213; Keeping 1995, p. 152). The basis of stratification for the current study is on King and Amponsah’s (2012) findings which showed, 50% of slum operators in Ghana are engaged in the manufacturing sector and 49% in services sector. These two sectors therefore, represent the two strata for the current study.
5.3.6 Sample size
As mentioned in section 5.3.1, there is no existing data on the number of operators in slum activities in Ghana. This makes it difficult in determining a representative sample size. In determining the sample size for the study, the researcher took into consideration sample requirements for factor analysis and principal component analysis. According to Gaur and Gaur, (2006) and Hair et al., (2010), the sample should be more than 100, whereas Tabachnick and Fidell (2013) suggest that a sample size of above 300 is appropriate for Factor and Principal component analysis. Therefore, 200 slum operators in each of the two slum regions will be selected using the stratified random sampling technique. A random sample of 200 respondents was to be selected from each slum and 100 from each activity, ensuring a fair representation of operators in both sectors (strata).
5.3.7 Data Collection Method
Data can be obtained by various methods, depending on the nature of one’s research; these include observations, interviews and surveys (Driscoll, 2011, p. 154). Observations entail the researcher witnessing the ‘world’ around him/her and measuring it, while interviews involve questioning participants in a research in either a small group setting or on one-on-one basis. Lastly, in surveys researchers ask participants questions about a specific phenomenon, mostly through a questionnaire.
A survey, according to Sapsford (2007, p. 3), is the process of describing a population to report
“what is there” as information collected; in Driscoll’s (2011, p. 162) words, is “self-reported”.
Survey method allows for direct comparison of cases since the same information is sought from
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each case leading to a structured data set. Since questionnaires are often highly structured, they are mostly used in surveys. The current study employs questionnaires in gathering data from the informal operators in the AL and S&G slums. Section 5.5 below covers in detail the subject of questionnaires.