<\/p>\n
Respond by Day 5<\/strong> to at least two<\/strong> of your colleagues’ postings in one or more of the following ways:<\/p>\n Classmate 1 (Amy) Post:<\/strong><\/p>\n “My final project will be a survey to measure several items in connection with selecting the right people for the right volunteer positions to make the organization more effective. The items surveyed will be personality traits, ability, interest and attitude. In order to measure these items, I will construct a questionnaire which will ask questions of both volunteers and guests. As a result, I hope to find the right volunteers are working in the right position and will experience less stress and burn-out and are considerably happier when they are utilizing their talents.<\/p>\n The three most important considerations related to sampling in my project are: sampled group, reliability and validity of the data (Anastasi, 1997). I would include the sampled group to be the population of interest as the volunteers. The results of the survey will be assessed for reliability and validity to ensure the long-term goals are met and if the goals are not met, then the questionnaire will be given to a second group and those results will be assessed to find out if the questionnaire needs to be changed or if the process needs to be changed (Tett, 2009). In assessing the relationship between the questionnaire and the results given by the questionnaire, the results can differ slightly as each individual has a different view (Sweney, 1962). The questionnaire is multiple choice and the individual should answer based on their initial thought, the researcher will find a slight amount of variance between the results. “<\/p>\n Classmate 2 (Kristopher) Post:<\/strong><\/p>\n “<\/strong> When conducting research, it is important to understand the population that one is examining. This is because it may be difficult or impossible to test the entire population. As a result, one will need to sample a smaller portion of the population to gather results. These samples must be representative of the population (Babbie, 2017). This can be achieved in many ways, however, they must follow certain guidelines so the data can be most accurate.<\/p>\n The sample size must be large enough to have a statistical significance to the larger population (Tett, et al., 2009). There are specific formulas that are designed to demonstrate a sample size that could be extrapolated to a larger population and maintain statistical significance. If a sample size is too small, there could be a lack of statistical significance when a correlation is present. This is known as a type 2 error (Jackson, 2005). If the sample size is too large, then it can consume too many resources and make the data gathering too expensive. For my proposed experiment, I will be focusing on the United States of America and its population. This is because personality types and consumer trends are culturally based (Hays, 2009). Extrapolating data to other cultures would introduce some confounding variables. As a result, the sample size should be dictated by the approximate population of the United States.<\/p>\n Another essential feature of sample significance is that the demographic data of the sample should meet the demographic data of the larger population being studied (Babbie, 2017). For example, the population of the United States is roughly 51% female; as a result, a similar demographic should be found in the sample. One way to ensure this kind of symmetry is to ask for demographic information in the assessment. Common demographic information includes sex, age, and ethnicity (Burkholder, 2016). This way it is possible to correlate the gathered sample data to the overall population census data. Because my specific area of inquiry has to do with personality type, it may be important to utilize other research to determine demographics of personality type so that there is an accurate representation of the number of different personalities in the population.<\/p>\n Randomized sampling is one of the most important parts of generating a sample. A random sample is where every individual of the population has an equal chance of being selected to participate (Burkholder, 2016). This has the unique effect of removing many extraneous variables that are unique to an individual participant. Let us say, for example, the survey is given over the Internet through a specific website. This means that individuals who either do not have the internet, do not have a computer, or do not have the knowledge to navigate to the website cannot participate. This would effectively reduce the randomization of the sample and decrease its overall quality of data. Another example of this is if participants are made to pay $100 to participate, then this would alter the demographic of people participating, such as individuals who value money less or individuals who have $100 to spend. The data gathered would be significantly skewed for the population being studied. However, it may not be entirely possible to have a fully randomized sample. Certain assumptions are made to reduce the number of resources spent on conducting research (Babbie, 2017). For example, it is assumed that most participants are literate and will not need a translator or a reader to participate in the assessment. If this were the case, then there would be a significant increase in resources that could be allocated.”<\/p>\n <\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":" Respond by Day 5 to at least two of your colleagues’ postings in one or more of the following ways: Ask a probing question. Share an insight from having read your colleague\u2019s posting. Offer and support an opinion. Validate an idea with your own experience. Make a suggestion. Expand on your colleague\u2019s posting. 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