HLT-362V Topic 3 Clinical Inquiry and Hypothesis Testing
Both hypothesis testing and confidence interval are essential in data analysis processes in the healthcare system. In healthcare research, hypothesis testing is a way of testing the survey results or an experiment to ensure meaningful results or outcomes. Hypothesis testing is a statistical method whereby researchers test the assumption about the population parameter. The methodology applied by data analysts depends on the type of data collected and the reasons for conducting analysis. Hypothesis testing is often applied in assessing the plausibility of a hypothesis through the application of sample data. On the other hand, the confidence interval refers to an estimate that is computed from the collected data; it gives a range of values for the unknown parameter, such as the mean. Confidence interval is drawn from the confidence level, which is always designated before examining or evaluating data. In most cases, a 95% confidence level is applied in the research processes (Ambrose, 2018).
Hypothesis testing and confidence interval can be used together in the data analysis process. The confidence interval can be applied to inform decisions on when to reject or accept the null hypothesis. Confidence interval involves a range of values that are always set around the mean, either negatively or positively. To reject the null hypothesis, 95% of the values should be set closer to the mean. The confidence interval can be used to reflect the risks of the researcher being wrong. Rejecting or accepting the null hypothesis is always based on the 95% confidence interval (Savage, 2018). In healthcare research, confidence interval may inform the researcher as well as the reader about the significance or power of the study and whether the data and results obtained represent treatment effects.
Ambrose, J. (2018). What are statistics and why are they important to health science. In Applied statistics for health care (1 ed.). Grand Canyon University: Grand Canyon University.
Savage, S. (2018). Advantages of confidence intervals in clinical research. Retrieved from: https://www.redorbit.com/news/science/18686/advantages_of_confidence_intervals_in_cl inical_research/
HLT-362V Topic 3: Clinical Inquiry and Hypothesis Testing
Evaluate hypothesis testing approaches and their application to health care.
Define dependent and independent variables and their role in hypothesis testing.
Describe evidence used to “reject “or “do not reject” the null hypothesis.
Evaluate the relationship between hypothesis testing and confidence intervals.
Read “Chapter 6: Research Design” and watch the associated videos, by Lane, from Online Statistics Education: An Interactive Multimedia Course of Study.
Chapter 10: Estimation
Read “Chapter 10: Estimation” and watch the associated videos, by Lane, from Online Statistics Education: An Interactive Multimedia Course of Study.
Chapter 11: Logic of Hypothesis Testing
Read “Chapter 11: Logic of Hypothesis Testing,” and watch the associated videos by Lane, from Online Statistics Education: An Interactive Multimedia Course of Study.
Chapter 12: Test of Means
Read “Chapter 12: Test of Means” and watch the associated videos, by Lane, from Online Statistics Education: An Interactive
Multimedia Course of Study.
Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial
Review “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 this article in conjunction with the “Article Analysis Example 2” document to help prepare for the article analysis assignment due in this topic.
Hypothesis Testing, Type I and Type II Errors
Read “Hypothesis Testing, Type I and Type II Errors,” by Banerjee, Chitnis, Jadhay, Bhawalkar, and Chaudhury, from
Industrial Psychiatry Journal (2009).
Probability, Clinical Decision Making and Hypothesis Testing
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Read “Probability, Clinical Decision Making and Hypothesis Testing,” by Banerjee, Jadhave, and Bhawalker, from
Industrial Psychiatry Journal (2009).
Understanding Null Hypothesis Testing
Read “Understanding Null Hypothesis Testing,” by Jhangiani and Chiang, from the online eBook, Research Methods in Psychology(2013), available on the BC Campus Open Ed website.
The Difference Between Quality Improvement, Evidence-Based Practice, and Research
Read “The Difference Between Quality Improvement, Evidence-Based Practice, and Research,” by Ginex, from ONS Voice(2017), located on the Oncology Nursing Society (ONS) website.
Identifying the Differences Between Quality Improvement, Evidence-Based Practice, and Original Research
Read “Identifying the Differences Between Quality Improvement, Evidence-Based Practice, and Original Research,” by Baker et al., from Journal of Emergency Nursing (2014).
Probability, Proof, and Clinical Significance
Read “Probability, Proof, and Clinical Significance,” by Skelly, from Evidence-Based Spine-Care Journal (2011).
Statistical Versus Clinical Significance in Nursing Research
Read “Statistical Versus Clinical Significance in Nursing Research,” by El-Masri, from Canadian Journal of Nursing Research (2016).
Article Analysis Example 2
Review this document in conjunction with the “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial” article to help prepare for the article analysis assignment due in this topic.
Article Analysis 2
Use the “Article Analysis 2” template to complete the Article Analysis 2 assignment.
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Scholarly Resources: Scholarly resources are written with a focus on a specific subject discipline and usually written by an expert in the same subject field. Scholarly resources are written for an academic audience.
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Adapted from “Evaluating Resources: Defining Scholarly Resources,” located in Research Guides in the GCU Library.
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