Question

Read the extract below and answer the questions below

Strawberry international wishes to conduct a research study using their employees as key participants. The organization maintains a global footprint and employs over 25 000 employees at several branches worldwide

2.1 Discuss the reasons why sampling such a population is necessary. (10)

2.2 Describe four types of non-probability sampling. (8)

2.3 Critically analyse the principles of simple random sampling. (12)

Answer 1

2.1 sampling large population is necessary because it makes shows that the outcome is reliable to the sample mean and result in the accuracy of outcomes.

Moreover, sampling a population that is large helps in sweeping out the outliers of the sample. Thus, a large population gives the real picture and characteristics of the employees. Also, sampling such a population helps in getting quality and precise mean as mean is important to determine research.

2.2 nonprobability sampling is a type of sampling which is accomplished keeping in mind the subjective judgment by the researcher rather than random selection.

Four types of nonprobability sampling are as follow:

1. Quota sampling: this type of sampling is aimed to get the sample by giving the priority to a group automatically. For example, choosing a group of people as a sample from the employees who are handicapped or disabled.

2. Convenience sampling: convenience sampling is done simply according to the ease or comfort. For example, picking up a sample of 100 employees from a canteen of an organization.

3. Purposive sampling: This type of sampling is a subjective sampling or judgemental sampling as it aims at selecting those units or groups by researchers through judgments. For example any particular department, group of people, event, data.

4. Self-selecting sampling: this type of sampling allows the organization or individuals to select itself in the process of sampling.

2.3 the principle of simple random sampling is that each and every sample has an equal probability of getting selected in the process. Simple random sampling has the principle of statistical regularity which means that when large units are being selected from a population, it possesses the same features or characteristics. Also, every unit has an equal opportunity of being selected as a sample which is quite fair enough.

Another principle is the inertia of large numbers, which means that the bigger or larger is the population size, the more chances are there of results to be accurate.