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sampling process
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Sampling is the raw resource which enables the quantitative researcher gain insight on the target population. In the past half-century, Haer & Becher (2012) note that surveys have become the ubiquitous data gathering devices serving many researchers purposes for assembling data in person or by mail. Nevertheless, the purpose of the survey is designed to gather valuable data, however, even more important is the design and in the way it is conducted ethically. Sampling strategies can be diverse depending on the resources and time available to a researcher. The surroundings in which the survey is conducted play in important role easy and participation which the data can be collected.
Sampling frames provide guidance and the ability to correlate linking in from of the survey goals to the population. This framing confirms that there is merit and meaning which coexist between the target populations. Haer & Becher (2012) concludes that the suitable sampling framing needs to be adopted only after understanding the surroundings of target populations. Essentially, outlining the goals of the survey by a random collection process of the target population is desired through the anonymous and rigorous surveying process.
The goal of quantitative research is to find relationships among variables which can be dependent or independent variables. Delıce (2010) categorizes the main efforts quantitative research to find reliability with generalizability to search and find these relationships among the independent or dependent variables depending on the type of multivariate statistics being performed. The goal is not force these variables into a relationship, but to openly receive the results and present representative statistics in select...
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... data. International Journal Of Market Research, 55(4), 2-13.
Pessalacia, J., de Oliveira Ribeiro, C., & Massuia, D. (2013). Themes and situations that cause embarrassment among participants in research in which questionnaires or interviews are used. Investigacion & Educacion En Enfermeria, 31(1), 70-77
Hunter, L. (2012). Challenging the reported disadvantages of e-questionnaires and addressing methodological issues of online data collection. Nurse Researcher, 20(1), 11-20.
Research
Boyd, B. K., Gove, S., & Hitt, M. A. (2005). Construct measurement in strategic management research: Illusion or reality?. Strategic Management Journal, 26(3), 239-257. doi:10.1002/smj.444
Eden, D. (2002). FROM THE EDITORS Replication, Meta-Analysis, Scientific Progress, and AMJ's Publication Policy. Academy of Management Journal. pp. 841-846. doi:10.5465/AMJ.2002.7718946.
...sis, which could make all results invalid. With any research projects, limitations will be present. It is important to attempt to eliminate some of these causes in order to complete a thorough, accurate study. In future projects, this study could go about researching the issue in different ways. Perhaps using a larger sample size would be conducive for accurate results. A larger sample size helps reduce and even out any possible errors caused by those who do not answer truthfully. Also, keeping the surveys mainly anonymous would help to receive more truthful and accurate responses from participants. Participants may be fearful of judgments on open interviews or phone interviews, which could affect responses. In order to obtain as accurate results as possible, a future study would need to find ways to survey participants in a confidential way that feels comfortable.
In the example above, the survey needed not only to be expanded but diversified. By including the women and other workers, you make the statistics more accurate because it represents the TV watching habits of ALL the company’s employees. However, if the company is very large, it would be difficult to interview every single employee. The solution to this problem is called random representative sampling.
Different styles of research are employed in research to safeguard that the facts are acquired to permit examiners to find resolution to the principal queries for the study correctly, therefore, evading uncertainty ( ). Acquiring relevant proof encompasses stipulating the type of proof mandatory in answering the query. Methodological designs encompass logical complications; therefore, matters of sampling, information gathering methods, and queries are secondary to the type of method used in research. Strategies are often compared with quantitative and qualitative research methods. Research and collective studies are often observed as principal specimens of quantitative research and are evaluated compared to the flaws and strong point of numerical, examination, and quantitative research methods ( ).
Two sampling methods include mail surveys and convenience sampling, a variation of a nonprobability sample. Mail surveys, inexpensive way to contact individuals over a large geographical area, provide anonymity to the respondent, and eliminate interview bias. Convenience sampling, a nonprobability sample, the only criteria is the convenience of the unit to the researcher, fast and uncomplicated, but the sampling error not determined.
There was also the confounding variable of the researcher being in the same room as the participant as the study was taking place, this may have had an effect on the results of the study as the participants may have facilitated or inhibited the performance of the
Quantitative research methods include information having numeric meaning, also measuring. Focus in this research strategy is on measurement and the comprehension of the relationship amongst variables (Lincoln, 2003). Quantitative analysis consequently depends and builds on statistical trials, for example frequency, mode, median, quantity and arithmetical procedure.
The advances in technology have provided a number of ways to collect and interpret data in regards to scientific research. According to Cope (2014) using paper and pencil surveys is the tried and true method of collecting data; However, technology is quickly becoming a popular and at times a more efficient way to collect data. The use of technology allows interpreting data to become simpler, allows the researcher to reach a larger sample group and quicker compared
Kelley, K et al. (2003). Good practice in the conduct and reporting of survey research. Oxford Journal. 15 (3): 261-266.
To do this analysis we used cross tabulation technique for finding association among variables. Initially we test that two variables are associated or not. If two variables are associated then we find strength of this association by appropriate statistic. Cross tabulations can be produced by a range of statistical packages, including some that are specialized for the task. By using the cross tabulation technique, in this section we will analyze the association between variables. We will also test the correlation among them. Here we will explain the summary of the results.
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
As it is impossible for researchers to study an entire population, sampling theory studies a target population under study. A target population refers to a group of individuals who meet the sampling criteria for a particular study. For example, male, 20 years with type 1 diabetes. The two different types of sampling design are probability and nonprobability sampling. Probability sampling is the type of sampling plan where each person in the population has an equal opportunity to be selected for the sample, whereas in nonprobability sampling methods, not every element or person in the population has a chance to be selected for a study. This type is a more common method used in nursing research because of the limitations of the availability of
Sampling the act, process, or technique of selecting a suitable sample; specifically : the act, process, or technique of selecting a representative part of a population for the purpose of determining parameters or characteristics of the whole population (merriam-webster.com). There are several types of sampling and we can put these into groups. In this essay we will look at 2 main groups: Human selection and Random selection in sampling. Opinion Polls, Convenience sampling, and Quota sampling are in the Human selection group. Simple Random sampling and stratified sampling are Random selection. If there are several ways of sampling, what are the positive and negative aspects of each of them?
There are advantages and disadvantages to researchers’ various sampling methods. Random sampling does a good job of representing an entire population. However, researchers may have difficulty establishing a full list of a given population. The time and the expense involved in doing this can make the task impossible. Also, separating members from their group for research can prove unsettling for the target. Another issue is that by the time researchers have completed a study using this method the parameters of the sample can change, nullifying research results.
OLLIER-MALATERRE, ARIANE; ROTHBARD, NANCY P.; BERG, JUSTIN M. Academy of Management Review (Oct2013), Vol. 38 Issue 4
This paper discusses different types of sampling techniques used in quantitative research. It begins by looking at probability sampling (also known as random sampling) before discussing non-probability sampling (non-random sampling). The discussion ends by looking considerations that should be made before selecting a sampling technique before concluding. Because quantitative researchers prefer probability sampling and only use non-probability on rare occasions the e...