Question

Question 2

Read the extract below and answer the questions that follow

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)
Additional research is required. Read, understand and supply Section 4:sampling

2.2 Describe four types of non-probability sampling. (8)
Additional research is required. Read, understand and apply section 4: sampling

2.3 Critical analyse the principles of simple random sampling. (12)
Additional research is required. Read, understand and supply Section 4: sampling

Answer 1

2.1. Strawberry International has a customer base of over 25,000. It plans to conduct a research study that will include its employees. Since the number of employees is large and scattered, it cannot go and directly consult each employee as this procedure will be tiresome and time-consuming. The best way to carry out the process is through sampling.

Sampling is the process of selecting a group of people from the population on which the analysis or study is to be conducted. Samples represent the population. It is expected that the samples will have the characteristics of the population from which they are drawn. Hence drawing a sample and conducting research will yield the same result as conducting the study on a population. Here the company wishes to involve its employees in the research study to come out with productive ideas. The employees are the key drivers of profit for the company. Involving them in the decision making will improve customer satisfaction which in turn will improve productivity. The research study involving the employees can also be used to get feedback from them regarding the functioning of the business. This can be used by the company to improve its working procedures and conditions.

Here Strawberry International can sample the employee population to find answers to relevant questions that they want to address. It can be used to reach a conclusion. It can also be used for solving problems. Since the population is large, it is better to go for sampling to reduce complexity.

2.2. FOUR TYPES OF NON-PROBABILITY SAMPLING

Non-probability sampling is a type of sampling wherein the probability of getting selected from the population is not equal for each of the individuals involved, that is, the probability of getting selected is different. The four types of non-sampling are as mentioned below:

a) Convenience Sampling: This is a type of sampling in which the sample for the study is chosen as per our convenience. For example; Imagine we have a supermarket. If we wish to get feedback from at least 100 customers. For this, we can actually get the first 100 people who visit the store to fill the questionnaire. Else we can get it filled from those customers whom we feel like is the best to fill it. We can even get 10 customers to fill the form in a day. Hence in 10 days, we will have 100 forms filled.

b) Snowball Sampling: It is a type of non-probability sampling wherein the samples are found out or suggested by the already existing people. The people who are already selected for the survey will suggest their friends or acquaintances. As more people join, more information can be collected.

c) Quota Sampling: This type of non-probability sampling involves dividing the entire population into various sub-groups and selecting an equal proportion of individuals from each sub-group.

d) Judgemental Sampling: This is a type of non-probability sampling wherein the respondents are chosen from a population-based on the researcher's knowledge and expertise. These respondents are chosen as per the wish of the researcher. This technique can be used when the researcher is sure that the selected respondents are the best to respond.

2.3. Simple random sampling is a type of sampling in which the probability of getting selected is equally likely to all the elements present in the population. The principle of simple random sampling is that every object has the same probability of getting selected. This helps in finding the solution by analyzing the samples rather than the population as a whole. But at times error can occur. This is because the sample chosen may not at times possess the characteristics of the population. At times the sample chosen will lead to bias. It is always important to remain unbiased. Bias can occur due to a large number of reasons. This can prevent the researcher from getting the desired output.

Random sampling also requires the complete population to be considered. The samples are drawn from this population. The sample drawn should be homogeneous. If we draw two samples from the same population, both should yield the same result. The samples are considered to represent the population. But at times they fail to do so which results in faulty results.

The population should be selected in such a manner that the characteristics are uniform throughout. Then only the principle of simple random sampling will get satisfied.