# Essays on Probability & Non-Probability Samples Coursework

The paper "Probability & Non-Probability Samples" is a great example of management coursework.   Probability samples ascertain that each and every subject under study has an equal chance of being selected at any given moment in time (Teddlie & Yu, 2007). It possesses a distinguishable attribute that each and every unit within a given population possesses a fairly-known non-zero probability of being chosen within a given set of sample base. The capacity to allow each and every subject a chance of being selected is indeed a positive attribute as it eliminates the possibility of researchers being biased and depend solely on their own personal opinions and desires in coming up with outcomes (Teddlie & Yu, 2007). Non-probability samples do not facilitate the given study outcomes to be generalised from the sample of a given population set (Smith, 1983).

It is important to note that non-probability sample; the researcher is expected to restrict their study outcomes to the individuals or elements that have been sampled only hence they are not provided with an opportunity to compute particular sampling statistics that avail information in regards to the precision set out in the end results. Main Benefits and Limitations of Using Non-Probability Samples in Management Research Benefits It is important to note that non-probability sampling forms a valuable set of sampling methodologies that can be effectively used in management research that seeks to adhere to such aspects qualitative; mixed and qualitative research designs (Mays & Pope, 1995).

In the course of adhering to qualitative designs, non-probability sampling methodologies like purposive sampling allows management researchers with a rather stronger theoretical rationale behind their specific choice of units that would be included in a sample base. Inconvenience sampling, the management researcher is allowed the audacity to choose specific units that are deemed to be convenient to them since they do not necessarily call for pre-planning of the selection process (Mays & Pope, 1995).

It is crucial to add that convenience sampling seeks to ensure that management researcher enjoys lots of ease evaluating the readily-available sources lists and accessibility of the subjects under study. Notably, such non-probability sampling as quota sampling seeks to ensure that the management research attains high levels of ease in the course of executing the sampling research surveys (Mays & Pope, 1995).

They are allowed to replace units or rather subjects understudy in the event that a respondent is not willing and able to cooperate in providing information. It is significantly less expensive and fosters a speedy collection of informational data. Judgmental sampling is yet another form of non-probability sampling techniques that presents a significant number of benefits to a management researcher at hand. Considering the fact that in this form of non-probability sampling method the researcher will select subjects or units understudy in regards to the readily-available information, it cuts down the overall cost and time that could have been spending in the preparation of samples (Nielsen, 2010).

More to this, the form allows researchers to involve definite and positive aspects that relate to stratification within the underlying sample. Nielsen (2010, p. 304) argues that non-probability sampling can be indeed useful in exploratory management research activities whereby its main objective rests with finding out whether specific operational issues or challenges actually exists in a much faster and affordable manner. It is especially applicable in the event that it is limited or even lack of research that supports a specific theory and sampling bias of particular non-probability sampling is used as a tool to help the management researcher to find solutions needed (Tansey, 2007).

In essence, non-probability sampling is mostly adopted due to the fact that the procedures adopted in the course of selecting the subjects to be studied to be included in a sample are far much faster; easier and affordable in comparison to when the management researcher opts to use probability sampling.

References

List

Arber, S., 2001. Designing samples. Researching social life, vol.2, pp.58-82.

Barendregt, C., Van der Poel, A. & Van de Mheen, D., 2005. Tracing selection effects in three non-probability samples. European Addiction Research, vol.11, no.3, pp.124-131

Mays, N. & Pope, C., 1995. Rigour and qualitative research. BMJ: British Medical Journal, vol.311, no.6997, p.109

Nielsen, S. 2010. Top management team diversity: A review of theories and methodologies. International Journal of Management Reviews, vol.12, no.3, pp.301-316

Ritchie, J., Lewis, J. & Elam, G., 2003. Designing and selecting samples. Qualitative research practice: A guide for social science students and researchers, vol.2, pp.111-145

Smith TFM 1983, "On the validity of Inferences from Non-random Samples", Journal of the Royal Statistical Society, vol. 146, pp 394-403

Schillewaert, N., Langerak, F. & Duhamel, T., 1998. Non-probability sampling for WWW surveys: a comparison of methods. International Journal of Market Research, vol.40, no.4, p.307

Schreuder, H.T., Gregoire, T.G. & Weyer, J.P., 2001. For what applications can probability and non-probability sampling be used? Environmental Monitoring and Assessment, vol.66, no.3, pp.281-291

Tansey, O., 2007. Process tracing and elite interviewing: a case for non-probability sampling. PS: Political Science & Politics, vol.40, no.4, pp.765-772

Teddlie, C & Yu F. 2007. Mixed Methods Sampling: A Typology with Examples. Journal of Mixed Methods Research, vol.1, no.1, pp. 77-100