Analyzing Different Approaches Of Sampling

this study is the use of convenience sampling, as previously mentioned. Black et al. (2000) make

Luker describes sampling through canonical social science research as a “systemic random probability sample”, with the goal of producing results that can then be apply and a general way. For example, with a research question that focuses on voting in a election, A canonical social science research question may trying to determine how many voters are expected to vote a certain way in a election. By using randomly sampling a certain number of voters could be surveyed the result can provide a general description of the voting trend of an entire populations with similar characteristic as the sample group. While I agree with Luker that sampling is important to both canonical qualitative and qualitative social science research, in the case of qualitative research, the word has different meaning.

According to Acharya, Prakash, Saxena, and Nigam (2013), sampling designs are classified into two categories: probability sample and non-probability sample. Probability sampling aids in the generalizability of the results because individuals in the population have an equal chance of being selected to participate in the study (Acharya et al., 2013). With the non-probability sampling method, every individual does not have the same chances of being included (Frankfort-Nachmias, & Nachmias,

Probability sampling, also known as random sampling, requires that every member of the study population have an equal opportunity to be chosen as a study subject. For each member of the population to have an equal opportunity to be chosen, the sampling method must select members randomly. Probability sampling allows every facet of the study population to be represented without researcher bias. Four common sampling designs have been developed for selection of a random sample: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling (Burns & Grove,

A population is the entire group to be studied and a sample is a portion of the population.

In this essay, I will appraise the sampling methods used in the following two case studies:

In Greyber, L. , Dulmus, C. , & Cristalli, M. (2012) article, it indicated that the sample size consisted of 59 children participates ages 6-16. Non-Probability sampling was used in this study, as most of the children sampled were referred from a child psychiatric outpatient clinic. According to Rubin and Babbie (2014), this type of convenience or purposive sampling is the

What type of sample is this and why? Because it is reasonable to believe that every 1000th member of the income tax return population will represent the entire population, this is an example of a systematic sampling (Bennett, Briggis, & Triola, 2009).

Random sampling: Operates on the principle that everybody should have an equal chance of being selected as part of the sample. This is significant because it ensures everyone has the same opportunity of being represented in a poll.

Sampling strategy is a focus on a smaller group to determine the conclusions of the larger population (Cooper & Schindler, 2014, p. 338). In this instance, the McMahon Group employed both focus groups and mail surveys as strategies to gather information and the dual approach produced relevant and valuable data for researchers.

When researchers select participants from several different parts of the population, they are selecting a

A group of individuals are selected from a larger group. Each member of the population has an equal chance of being selected as a subject. For example, the lottery method. Each person from the population are given a unique number. Each number is placed in a container and mixed thoroughly. Without looking the researcher picks a number out of the container. Anyone who has the

-The sampling distribution is a distribution of the results if all possible samples are selected, where as a population distribution is the distribution of a particular variable of interest.

According to Hair et al. (2003), in the research, the sampling process enables identifying, developing and understanding an interested object that need to be determined (p.333). Hence, in order for the researcher to carry out the sampling appropriately, advantages and disadvantages of the various sampling methods should be considered along with the theoretical component of the study (Hair et al. 2003, p. 368 f). Theoretically, the sampling procedure is divided into two major types which consist of probability and nonprobability sampling. In probability sampling, individuals have a known chance of being selected. While, in non-probability sampling, individuals do not have a known possibility to be selected (Sekaran 2003, p. 269 f). Also, the different sampling methods provide different advantages and disadvantages. Hence, the researcher should consider this point before choosing the sampling method for the

Which of the following is true regarding non-sampling errors? A. it is important to know the possible causes of non-sampling error so that appropriate steps may be taken to limit their occurrence.