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The role of SMEs in rwanda from 1995 to 2010

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par Clotilde MUKAMUGANGA
National University of Rwanda - A0 2011

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3. 5.Sample size and selection techniques

The study must consider a sample size that is within the cost constraint but should provide the ability to detect an independent variable effect (Christensen, 1991: 372). Williamson (1982:113) comments on the sample size as being a phase of research, which is crucial because of its major impact on time and money that must go into data collection.

While selecting the sample size of the study; the researcher purposely five respondents particularly; representing all staff members. Data is collected from selected respondents from the study population due to the reasons of necessary and convenience.

3. 5. 1. Stratified sampling

The study population was stratified into two strata, one stratum was comprised of staff members of selected small and medium enterprise and the one was comprised of the population around that enterprise. From these two strata, the researcher used both simple random and purposive sampling techniques as these enabled her to select respondents who could provide her with the information needed for the study.

3. 5. 2. Simple random sampling

Simple random sampling was used to select enterprise. Simple random sampling as defined by Baker (1988:148) refers to the situation whereby each individual case in the population theoretically has a chance of being selected for the sample. The simple random sampling technique is used to select enterprise.

3. 5.3. Purposive sampling

Bailey (1978:83) explains purposive sampling technique as a technique whereby the researcher uses her own judgment about which respondents to choose and picks only those who can best meet the purposes of the study.

The formula of Alain Bouchard as cited by SABITI Fred (2004: 46)

where, No = t2(p)(1-p)/d2

n is the sample size, N is the size of the population, No is the sample size of a defined population, d is the error term that is estimated 5%, p is the estimated frequency of the sample with size n, while t is the figure obtained from the t-student's table.

Therefore, basing on the above formula, the researcher decided to use 95% as the confidence level of which Alain Bouchard says is more reliable. Thus, p=0.5, N= 45,000, d= 5% = 0.05, t=0.55

No= (0.55)2(0.5)(0.5)/(0.05)2=31 thus n =31/1+31/45000 = 30

It was on this ground that the researcher selected 5 staff members and from the enterprise 30stackeholders of it. The researcher's intention was to ensure that the sample includes the elements that are directly relevant to the problem being investigated /studied.

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