Describe the application of statistics in health care quality, safety, health promotion, and leaders
Question 1 :Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in nursing practice and with patient interactions.
Question 2: Evaluate and provide examples of how hypothesis testing and confidence intervals are used together in health care research. Provide a workplace example that illustrates your ideas.
please use article https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996198/
No Article less than 5 years old
ANSWER
Hypothesis Testing
Question One
Hypothesis testing has become significant in healthcare provision because it is half the answer to any research question. The two different examples of hypothesis testing engage null and alternative hypotheses. Null hypothesis documents that there is no link between the predictor and outcome variables in the population (Banerjee et al., 2009). Null hypothesis still acts as the formal basis for statistical testing significance. On the other hand, the alternative hypothesis cannot be tested directly and only accepted through exclusion if the statistical importance test rejects the null hypothesis. The criterion is called alpha, which is generally set to .05. If there is less than a 5 percent chance of a result as extreme as the sample if the null hypothesis were correct, then the null hypothesis is rejected. When this occurs, the outcome is said to be statistically significant. Rejecting the null hypothesis is essential in nursing because it is vital to avoid type 1 errors.
Question Two
Medical providers often depend on evidence-based medicine in their decision-making processes. Research hypotheses are tested with outcomes presented, usually with p values, confidence intervals, or both. Health practitioners need research questions and hypotheses to guide their evaluations (Killeen, 2005). These people will examine a gap in the current clinical practice or research with broad research questions. For example, hypothesis testing can prove if a given drug is essential for treating a given ailment. From the same perspective, confidence interval provides a range of values within absolute confidence, which involves the accurate value of the specific population’s statistical restriction. For example, research with 95 percent shows that if a study were to be done 100 times, the range would contain the actual value.
References
Banerjee, A., Chitnis, U. B., Jadhav, S. L., Bhawalkar, J. S., & Chaudhury, S. (2009). Hypothesis testing, type I and type II errors. Industrial psychiatry journal, 18(2), 127–131. https://doi.org/10.4103/0972-6748.62274
Killeen, P. R. (2005). An alternative to null-hypothesis significance tests. Psychological science, 16(5), 345-353.
