Assignment: Sampling Distribution HLT 362
Assignment: Sampling Distribution HLT 362
Assignment: Sampling Distribution HLT 362
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The sampling process is essential in the quantitative research processes. The process of sampling allows researchers to identify potential participants to be included in the research process. The study, “Comparing the effects of interactive and non-interactive education using short message service on treatment adherence and blood pressure among patients with hypertension.” by Pour et al., (2020), aims at comparing the impacts of non-interactive and interactive SMS (NISMS)-based education on blood pressure and treatment adherence among patients with hypertension (HTN). To enhance the efficiency of the study, a sample size consisting of 63 hypertensive patients was randomly selected to take part in the study process. The findings from the study showed that ISMS-based education is effective/essential in significantly enhancing treatment adherence among patients suffering from hypertension. On the other hand, NISMS-based education did not show any significance on treatment adherence among the study respondents. Further, the research findings showed that neither non-interactive nor interactive NISMS-based education is essential/effective in reducing DBP and SBP among the patients suffering from hypertension.
A stratified sampling method was used in this study to identify study participants. The target population was initially divided into subgroups; the selected participants shared similar characteristics (Zhao et al., 2019). The sampling method was used because researchers expected measurement of interest to vary between the subgroups that were supposed to be used. Also, there was the need to ensure effective representation of all the subgroups in the study process. The stratified sampling method is effective because it provides better coverage to the population under consideration in the research process (Liberty et al., 2017). Also, with the stratified sampling method, researchers have often had control over subgroups that are used first to classify respondents.
Liberty, E., Lang, K., & Shmakov, K. (2017, June). Stratified sampling meets machine learning. In International conference on machine learning (pp. 2320-2329). PMLR. http://proceedings.mlr.press/v48/liberty16.html
Pour, E. R., Aliyari, S., Farsi, Z., & Ghelich, Y. (2020). Comparing the effects of interactive and non-interactive education using short message service on treatment adherence and blood pressure among patients with hypertension. Nursing and Midwifery Studies, 9(2), 68. https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a-epidemiology/methods-of-sampling-population
Zhao, X., Liang, J., & Dang, C. (2019). A stratified sampling-based clustering algorithm for large-scale data. Knowledge-Based Systems, 163, 416-428. https://www.sciencedirect.com/science/article/abs/pii/S0950705118304581
For a normal distribution that has a mean of 100 and a standard deviation of 8. Determine the Z-score for each of the following X values:
X = 108
X = 112
X = 98
X = 70
X = 124
Use the information in 1 A to determine the area or probability of the following:
P(x > 108)
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