Sampling and Data Collection

Sampling and Data Collection.

Sampling and Data Collection

There are two main factors that determine the focus of the research within the methodology section. These include sampling and data collection. Apparently, these factors have a direct impact on the credibility of the results obtained from the research (Shaughnessy, Zechmeister, &Zechmeister, 2002).Furthermore, it is very important for the researcher to ensure that the sample chosen is fairly representative of the target population. In this section of the mock study, the sampling technique will be discussed alongside the sample size as well as statistical power. Additionally, the most appropriate data collection technique will also be explored.

The purpose of sampling in every research project is to use a proportion of the population that is deemed to be a fair representation of the target population. This is usually to ensure that the results obtained can be generalized to the population with minimum chances of bias (Vogt, 2007).This is called the external validity of the results since inferences about the population are drawn from a sample. There are various methods through which samples are collected, that is, probabilistic and non-probabilistic sampling. This research study will utilize probabilistic sampling since the intention is to generalize results on the correlation between transformational leadership practices and employee engagement. The latter method may be convenient but faces scientific validity concerns due to its subjective nature.

Under probabilistic sampling, there are four main approaches that are used. These include simple random sampling, stratified sampling, cluster sampling, and systematic sampling. These methods are efficient in controlling for some of the confounding variables that may affect the reliability of the results obtained. In the current study, systematic sampling will be employed. By definition, systematic sampling is the process of randomly selecting a sample through a sequentially selecting the sample units (Black, 1999).This method entails establishing the population size in the area of interest after which the researchers picks an integer at random that is less than the population size. This integer is then assigned to the first sample unit. Thereafter, every nth unit in the population is selected into the sample. This method is known to increase the external validity of the results since the sample units are selected evenly from the population (Christensen, Johnson, Turner, 2011). Moreover, the systematic approach will be applied in the current study because the human bias is eliminated in the selection of sampling units, which increases the reliability of the results.

The target population of leaders in the organization in the locality is estimated to be about 1,500. Therefore, the researcher will pick about 300 leaders at random to participate in the study. To achieve this through systematic sampling approach, the researcher will create a list of all the leaders who are assumed to have transformational leadership practices in their organization, assuming the population of 1,500 leaders. Secondly, this will entail selecting an integer at random between 1 and 1,499 and the integer will represent the first person to be represented in the sample. Finally, every 5thperson will be selected from the list to attain the desired sample size of about 300 leaders. This sample size will be deemed to be adequate since it is large and chosen using a probabilistic approach. Furthermore, it will ensure that most characteristics of the population, if not all, are captured in the sample.

Another important aspect that the researcher is supposed to take into consideration is the statistical power of the test. This is a representation of the strength as well as the validity of results based on the sample information. By definition, statistical power is the probability of avoiding type II error, where type II error is the likelihood of accepting a false null hypothesis. Statistical power is typically affected by two factors namely sample size and the level of significance of the hypothesis test. Sufficiently large sample sizes warrant higher statistical power. More so, when the level of increases, the power of the test also tends to increase although this increases the likelihood of committing type I error.

Regarding data collection, information will be obtained through the Multifactor Leadership Questionnaire. The questionnaire will be administered to the leaders physically by the researcher as well as online for those who will not be accessed physically. There are several advantages of collecting data through the questionnaire. These include but not limited to ease of analysis, familiarity among leaders, information can be obtained from a large sample at relatively low costs, and the non-response rate is reduced significantly.






Black, T. R. (1999).  Doing quantitative research in the social sciences: An integrated approach to research design, measurement, and statistics.  London, England: Sage Publications.

Christensen, L. B., Johnson, R. B., & Turner, L. A. (2011).Research methods, design, and analysis.  Boston, MA: Allyn& Bacon.

Shaughnessy, J.J., Zechmeister, E.B., &Zechmeister, J.S. (2002).Research methods in psychology.  New York, NY:  McGraw-Hill Higher Education.

Vogt, P. R. (2007).  Quantitative research methods for professionals.  Boston, MA:  Pearson.


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Sampling and Data Collection

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