Measuring The Quality Of A Hip Prosthetic Implants For Specific Breeds Of Dogs Essay

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,

The compiled data was used to form population A of the experiment, while population B was predetermined and provided by the instructor. Research was conducted using primary sources and data collected in order to locate evidence supporting the hypotheses.

“For an accurate estimate of the relationship between variables, a descriptive study usually needs a sample of hundreds or even thousands of subjects” (The Association for Educational Communications and Technology). The estimate of the relationship is less likely to be biased if you have a high participation rate in a sample selected randomly from a population.

The number of participants in this study in each condition was 20. This is a quarter of the number of participants in the Chen et al study, which had 80 participants in each condition. Byford (2014) states that it is difficult to take the results of a small sample size and apply the results to the general population, and therefore one must be prudent when applying these results to a project or advertisement.

This article will help me compare the chances of joint disorders and cancers when dogs are neutered early and late as well as intact. For example, I would use, “out of three hundred fifty-nine male dogs with hip dysplasia one hundred thirty-eight were intact, one hundred fifty-six were neutered early, and sixty-five were neutered late” (Torres de la Riva 5). Sixty-nine late-neutered, one hundred sixty-nine early-neutered, and one hundred twenty-two intact females were diagnosed with CCL (Torres de la Riva 5). Another example is: Three and thirty-nine hundredths of dogs with lymphosarcoma were intact and three and sixty-seven hundredths were early-neutered (Torres de la Riva 5). This article shows no matter the time a dog is neutered the chances of cancers and joint disorders go up (Torres de la Riva).

Many randomised controlled trials involve large sample sizes because many treatments have relatively small effects. The size of the expected effect of the intervention is the main determinant of the sample size necessary to conduct a successful randomized controlled trial. Obtaining statistically significant differences between two samples is easy if large differences are expected. However, the smaller the expected effect of the intervention, the larger the sample size needed to be able to conclude, with enough power, that the differences are unlikely to be due to chance

In population-based studies, instead of looking at a small group of individuals to make an assumption on the entire population, we are taking numbers that represent the population and determining

To ensure the results of the research are ethical and valid a proper sample design is necessary. A sample design consists of methods, sample frame, and sample size.

According to Machado et al. the population size for this study was 300 elderly people, of the population a formula for studies with groups was adopted with a 10% increase for losses and refusals (2017). This resulted in a sample group of 145 elderly persons that completed the study (Machado et al., 2017). Polit & Beck explain that the larger a sample size in relation to the population size, the less likely it is for a sampling error to occur (2017). In this case, the sample size appears to be sufficient to represent the population elderly people with

When doing any research studies, there must be enough participants to make the sample representative of the target population and to also determine an anticipated effect size. However, 120 individuals (60 men and 60 women) are also being tested in order to maintain an equal gender balance in both groups for the study.

Was the sample approach adequate for the research design that was selected and explain why.

“One method of determining sample size is to specify margins of error for the items that are regarded as most vital to the survey” (Cochran, 1977). If a researcher was doing a study on the effect the Glass Ceiling has on women’s careers and the researcher used a sample of rich, single men, the sample group would not remotely be an accurate assessment of the population the research was attempting to study. Therefore, it is extremely important for a researcher to be specific with their sample size requirements prior to acquiring one otherwise the study would be inaccurate and not a scientific

From G*Power it explains, the sample size will be significant and good sample size. I used alpha .05 and .80 for power then I added my population size in the program (Faul, Erdfelder, Lang, & Buchner, 2007). The sample size for this population in the health program has to be a good size and well rounded. I want to achieve good data and realistic sample size. The response rate I anticipate from this population is to be 70%. The reading level needs to be around .07-.08 for literature purposes and reliability for each participant in the health program (Faul, Erdfelder, Buchner, & Lang, 2009). To collect data for this survey I will use paper and pencils for the

The project aim at teenagers, therefore sample group is between 13 to 19. I will set the sample sizes in 50 participants since it is easy to identity and more precision. If a sample sizes increase, it is very hard to estimate and become not accurate. Also, I’m worry about the extremes data can’t make a balance out, so the project prefers small sample sizes. It can take less effort to gain and maintain people, it is easy to produce significant results and comfortable to find a group of people. I will obtain samples from friends or friends’ sister and brother.