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Amanda Williams

From attendance research conducted at concerts held by the Glacier Symphony during the previous two years, you can obtain gender data on attendees for each type of music. How would you conduct a reasonably reliable nonprobability study?

Less effort and time is spent by the researcher when using nonprobability sampling. Nonprobability sampling is a technique which allows the samples to be gathered in a process. This process does not give everyone a fair chance at being selected (Non-Probability Sampling, n.d). Nonprobability sampling is known to be less superior, inferior even to probability sampling, and the significant advantage of being more cost effective (Cooper & Schindler, 2014). There can be room for bias when utilizing nonprobability sampling. The bias is known to affect the surveyor when choosing the sample pool, it is no longer randomized like it is when using probability sampling. Another is bias lies with the respondents themselves. They may choose to not complete the survey which may tamper with a true view of the results.

With 200 concerts coming up at the Glacier Symphony within the next year, a “reasonably reliable nonprobability sample” has been requested. Research from the past two years can be used for the nonprobability sampling. This research will provide the gender of each attendee at each concert and the music genre. We also know how many tickets are available for each concert.

As stated earlier, nonprobability sampling is much more cost effective than probability sampling (Cooper & Schindler, 2014). There are several types of nonprobability sampling that can be done. The most effective for Glacier Symphony would be the use of a Quota Sample. A Quota sample will allow a researcher to sample a subgroup and allows the researcher the opportunity to watch the relationships between subgroups (Non-Probability Sampling, n.d.).

Luckily, the Glacier Symphony has data from the past two years which can be used and will be very helpful. It can provide the researcher with the gender of the population at each concert and what kind of music genre was played as well. When using this data to populate a nonprobability sample, the gender of the population should be more of the constant and the variable should be the type of music. For example, if you have 70% women and 30% men, the results will be skewed. However, if you have 50% men and 50% women, the music genres will be equally represented by both men and women. Cutting out any concern of bias against gender will provide a well-rounded sample and allow for more accurate results. Feild et al reminds us that nonprobability sampling makes it impossible to determine if there are any sampling errors (2004).

This week, incorporating a bible verse has been difficult for me. While considering what to use here I thought to myself that we are all very lucky, God has no variables and prefers a nonprobability sample when it comes to us as his followers. Remember that all he asks is for you and I to believe in him. John 3:16 says, “For God so loved the world that he gave his one and only son, whoever believes in him shall not perish but have eternal life” (New International Version).

References

Cooper, D., & Schindler, P. (2014). Business research methods (Twelfth ed., p. 537). New York, NY: McGraw-Hill.

Feild, L. (2006). Using Probability vs. Nonprobability Sampling to Identify Hard-to-Access

Participants for Health-Related Research: Costs and Contrasts. Journal of Aging and Health,18(4), 565-583. doi:10.1177/08982643062914

Non-Probability Sampling. (n.d.). Retrieved December 06, 2016, from