HLT-362V Topic 2: Population and Sampling Distributions
HLT-362V Topic 2: Population and Sampling Distributions
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There is a growing body of evidence that suggests that being vigilant about one’s race can have adverse consequences for health, including obesity. A study published in 2018 looked at the relationship between race-related vigilance and obesity status among African American adults.
The study found that those who reported being more vigilant about their race were more likely to be obese. This suggests that the stress associated with constantly having to monitor one’s race can lead to weight gain (Powell et al., 2018). This research is important because it underscores the importance of addressing the stressors that contribute to obesity in minority communities. Addressing these stressors will require collaborative effort from policymakers, healthcare professionals, and community members. Only then can we hope to see meaningful reductions in obesity rates among African Americans.
From the study, there was the application of stratified sampling method to identify study respondents. The stratified sampling method is a type of probability sampling where subjects are first divided into strata, or groups, and then a random sample is selected from each stratum. This method ensures that each stratum is represented in the final sample and allows for more precise estimation of population parameters. From the study, African Americans were first divided into strata where random samples were selected. The effectiveness of stratified sampling depends on a number of factors, including the nature of the population being sampled and the specific aims of the research. However, in general, stratified sampling can be an effective way to obtain a representative sample from a population.
One advantage of stratified sampling is that it can allow for more precise estimates than simple random sampling, particularly when strata are relatively homogeneous. This is because combing data from multiple strata can provide more information about each stratum than would be available from a single randomly selected sampled unit from that stratum. In addition, stratified samples can be easier to work with and process than complex random samples.
There are a few potential disadvantages of stratified sampling that should be considered before deciding whether or not to use this method. First, stratified sampling can be more time consuming and expensive than other methods since it requires extra steps to ensure that each stratum is represented proportionately in the final sample. Additionally, if the population includes a large number of strata, it may be difficult to create an effective sampling plan. Finally, there is always the potential for human error in any data collection process, and stratified sampling is no exception. If errors are made when categorizing individuals into strata or when selecting which members of each stratum to include in the sample, it could jeopardize the validity of the results.
In conclusion, stratified sampling is essential in any study because it allows for a more accurate representation of the population. By dividing the population into strata (or groups), researchers can ensure that each stratum is adequately represented in the sample. This helps to avoid bias and ensures that the results of the study are more representative of the entire population. The stratified sampling method is a type of probability sampling where subjects are first divided into strata, or groups, and then a random sample is selected from each stratum.
Reference
Powell, L. R., Jesdale, W. M., & Lemon, S. C. (2018). On edge: the impact of race‐related vigilance on obesity status in African–Americans. Obesity science & practice, 2(2), 136-143. https://doi.org/10.1002/osp4.42
Description
Objectives:
Identify examples of descriptive and inferential statistics.
Describe strategies for selecting a sample from a population.
Identify key questions you will ask/answer when reading a research study.
Study Materials
Applied Statistics for Health Care
Description:
Read Chapter 2 in Applied Statistics for Health Care.
Chapter 9: Sampling Distributions
Description:
Read “Chapter 9: Sampling Distributions,” and watch the associated videos by Utens et al., from Online Statistics Education: An Interactive Multimedia Course of Study.
The Visual Learner: Statistics
Description:
Refer to the “Visual Learner: Statistics” to learn more about the statistical calculations presented in this topic.
Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial
Description:
Read “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial,” by Utens et al., from International Journal of Nursing Students(2013).
Review article in conjunction with the “Article Analysis Example 1” document to help prepare for the article analysis assignment due in this topic.
Eight Questions to Ask When Interpreting Academic Studies: A Primer for Media
Description:
Read “Eight Questions to Ask When Interpreting Academic Studies: A Primer for Media,” by Feldman and Wihbey (2015), located on the Journalist’s Resource website.
Ten Scientific Questions to Ask About Scientific Studies
Description:
Read “Ten Scientific Questions to Ask About Scientific Studies,” by Smith, from Greater Good Magazine (2015).
Research 101: Descriptive Statistics
Description:
Read “Research 101: Descriptive Statistics,” by Conner and Johnson, from American Nurse Today (2017).
Tasks
You must proofread your paper. But do not strictly rely on your computer’s spell-checker and grammar-checker; failure to do so indicates a lack of effort on your part and you can expect your grade to suffer accordingly. Papers with numerous misspelled words and grammatical mistakes will be penalized. Read over your paper – in silence and then aloud – before handing it in and make corrections as necessary. Often it is advantageous to have a friend proofread your paper for obvious errors. Handwritten corrections are preferable to uncorrected mistakes.
Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages.
Likewise, large type, large margins, large indentations, triple-spacing, increased leading (space between lines), increased kerning (space between letters), and any other such attempts at “padding” to increase the length of a paper are unacceptable, wasteful of trees, and will not fool your professor.
The paper must be neatly formatted, double-spaced with a one-inch margin on the top, bottom, and sides of each page. When submitting hard copy, be sure to use white paper and print out using dark ink. If it is hard to read your essay, it will also be hard to follow your argument.
