Biostatistics: Hypothesis Testing. Health, Medicine, Nursing Essay
The purpose of this assignment is to evaluate the steps of hypothesis testing.
Hypothesis testing is a central component in understanding and interpreting public health research. Research questions are applied through a testable hypothesis established before the data is collected. It provides the rationale for the study and guides the researcher in what tests to use and how to interpret the results.
Identify a peer-reviewed article from one of the data sources available on the "Data Resource Document." You will need to visit the various websites listed on the document to search for a research article that is of interest to you. Include the link to the selected article in a 750-1,000 word summary that address the following as it relates to the article.
What test statistic did the researchers use? What did the authors set as the significance level of the test statistic?
What was the null hypothesis? What was the alternative hypothesis? Were these clearly stated in the article, or did you have to extrapolate based on the background in the article?
Discuss potential bias that may have resulted from the study design and data collection that could have affected the validity of the test.
Summarize the story told by the data used in this study as it applies to the larger population
Comment on whether the authors used the interpretation approach discussed in the textbook, including (a) summarize why the study was done, (b) discuss the factual results, (c) explain what the results mean, and (d) make suggestions for future research.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.
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What test statistic did the researchers use?
The use of t test statistic was evident for the two studies utilized in this paper. Kann et al. (2018) study was analyzing the high-risk behaviors’ contribution to morbidity and mortality among the youth and adults in United States. The researchers used the t tests to determine to determine the pairwise correlation and differences between the subpopulations (sex, race, grade, sex of sexual contact and sexual identity). The other study by Kessaram et al. (2016) on alcohol use in the Pacific region with key focus on drinking patterns amongst adults aged 25-64 also utilized he t test. The t tests were used to identify whether the frequency of drinking by sex was a cause for death across twenty Pacific Island countries and territories (PICTs) using three standardized surveys.
The significance level of the test statistic
Researchers who conducted a survey on the Youth Risk Behavior all used t tests having a p value of <0.05 being statistically significant. For instance, Kann et al. (2018)’s study looked at the health-risk behaviors leading to morbidity and mortality among youth and adults in the U.S. The authors used a logistic regression analysis to estimate the variables and 95% confidence interval for association between variables. In analyzing alcohol use in the Pacific, Kessaram et al. (2016) used a 95% confidence interval to find the correlational between variables with coefficients having a p value of <0.005 being statistically significant.
Were these clearly stated in the article, or did you have to extrapolate based on the background in the article?
Both the null and the alternative hypothesis were noted in the studies, although the authors did not clearly indicate and distinguish between the two. Therefore, although I extrapolated the hypothesis from the article, some vivid leads pointed to where they were to be found.
The null hypothesis
Health-risk behaviors did not contribute to leading causes of morbidity and mortality among adults and the youth in U.S. (Kann et al., 2018). This implies that health behaiors such as sexual related to unintended STIs and pregnancy, tobacco use, alcohol use, unhealthy dietary behaviors and physical inactivity did not lead to death.
Alcohol use is not a leading risk factor for injury and disease in PICT (Kessaram et al., 2016). There was no relationship between current drinking, heavy drinking, sex of drinker and region to alcohol use.
The Alt...
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