Sampling Vs. Stratified Random Sampling

Social stratification is defined as a system by which society ranks categories of people in a hierarchy. For example, There are fundamental principles of stratification:

According to Schutt (2008), sampling is defined as a subset of population used in a study to be a representation of the population as a whole. My final project is a pre-hire assessment which analyzes potential risky pattern behaviors and emotions in the work place. One of the most important considerations related to sampling that will need to be addressed in my final project is defining the population that will be taking the assessment.

Random Sample: A sample in which every “person of interest” has an equal chance of being selected into your research study.

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,

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.

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

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.

c. A non-random sampling is more convenient because getting data by putting up flyers is easier than looking through the entire population of SJSU.

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.

Our research question is “Does having a significant other effect how many hours University of North Georgia-Dahlonega students study during the week?” We hypothesized that having a significant other would negatively affect students’ study time as they would devote more time to their personal romantic lives and less to their academic careers. To test this hypothesis, our group conducted a Stratified Random Survey of UNG-Dahlonega students.

surveyed and randomly distributed across the study area stratified by increasing, and decreasing by randomly selected numbers along the grid. In a manner that ensures every plot has an equal likelihood of being

Another randomly selected number from 1 to 25 is chosen to be the interval value n. Each sample contains the first member and each subsequent nth survey until the sample size is reached. This method is simple; each survey response is given an equal probability of being selected, and the whole population of surveys will be evenly sampled.

This method would be more appropriate than stratified sampling, as I want each group to be the same, regardless of where they are from. Stratified sampling would allow me to represent groups based on male-female ratios per town or city, but since each group is going to be assigned an equal number of participants, cluster sampling is the better option. From this point I will use a two-step version of systematic sampling. First, I will break up the groups into male and female categories, and then use systematic sampling within these divisions to choose which participants to study. Considering that this experiment does not entail administration of medication or other physical items, I could stop after breaking up the population into clusters, but for the sake or narrowing down my participatory groups as well as cost savings, it makes sense to further narrow down prospective

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

The sample selection technique is stratified systemic random sampling technique where each ward of the city represents a stratum, using probability proportional to size technique.