Sampling Methods Essay

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

The researchers used purposive sample but did not give any explanation as to why this choice sampling was made. It is essential to describe the sampling process in a research where this facilitates the reader to distinguish any bias in the whole sampling process. In studies using participants, the process of how to select, access, inform and retain research participants requires considerable thought. Sampling is a key issue, because it is

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,

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

This section will provide the rationale of the methods employed and highlight how the study will be performed. The study will examine the population with the sample size identified, data collection method and its analysis will be offered.

The sampling of the observed subjects was obtained through the sampling design of Quota Sampling. According to Polit and

*For accurate inference, researchers need to analyze data drawn from representative samples. Discuss some of the practical limitations to doing so for qualitative and quantitative approaches.

Convenience sampling is a process of selecting participants for examination and analysis based on their accessibility, ease, speed, and low cost. The participants are often not purposefully or strategically selected (Brewis, 2014).

Lind, D. A. (2005). Statistical Techniques in Business & Economics (12 ed.). New York: The

Sample (sampling techniques, sample size, sample characteristics) Two authors independently reviewed the references to identify studies for inclusion and extracted data to assessed risk of bias in all included studies.

When conducting a study, it is impossible to collect data from the whole population, therefore it is important to select a representative sample because sampling makes it possible to select a representative for study and discover things that apply to many more people who are not studies (Maxfield & Babbie, 2012). The purpose of sampling is to generate a set of individuals or other entitles that give us a valid picture of all such individual or other entitles. It is important to generalise from a sample to unobserved population the sample in intended to represent. Therefore, when selecting a group of subjects for study, it is important to ensure that we represent some larger population.

The population for this study is women who delivered and are breastfeeding. The reason I chose this sample is because I will be able to survey the sample to see if the mothers received education on the benefits of skin to skin contact during their prenatal classes. If they received information on skin to skin contact, they can answer questions on how that influenced them to breastfeed. A chart review would also be done to see if the mother did skin to skin then breastfeed. This group of women who did skin to skin and breastfeed would be classified as stratified random sampling because they are a subgroup of a population that delivered. Stratified Random Sampling is when a population is divided into subgroups or strata (Patton, 2014). According to Patton (2014), stratification is based on a variable that is relevant to the issue being studied.

A. Sampling is a selection of a smaller percentage of individuals from within a larger population that is used to estimate the attitudes and characteristics of the whole population. Sampling saves time and money which is always a good thing, and allows for more manageable research. It may be almost impossible to identify every member of a population/group some may be too large, for example, if you were conducting a study on high school students as to whether they bring lunch to school or eat at the cafeteria, and this research was conducted for the entire state of Texas. Well, it would take an enormous amount of manpower and money to survey every single high school student in the state plus you would have other factors to consider as well. Then you would run into managing issues with such a large endeavor, so choosing a sample or small representation of individuals from the larger population is more

The participants of clearly the individuals from three separate cohorts, however the researchers do no specify if all individuals in each of the three cohorts are sampled or if only a portion of them participated in the research. This is an important issue that needs to be addressed by the researchers, although the number and sex of participants from each cohort is reported, the differences in sampling selections could present a significant difference in the conclusions obtained from the research data.