Hypothesis testing and confidence intervals are used together in health care research. With confidence interval (CI), this is used as an interval estimate for the mean. CI is a range of values that are set close to the mean and can impact the direction either positively or negatively (Ambrose, 2018). CI are used for means using a procedure that contains the population mean with a specified proportion of the time, typically either 95% or 99% of the time (Lane, n.d.). The CI is the interval that the researcher can be wrong. CI of 95% shows that 95% of a research study will include the true mean, and the other 5% will not be true (Ambrose, 2018). For example, in a test survey of 100 participants, 95% of the collected data will be right and five out of the 100 will be wrong. If the 95% is reduced, this increased the risk for error (Ambrose, 2018). This is important to consider with health care research because hypothesis testing and confidence intervals are used together.

For example, if you wanted to know the mean of temperatures collected in a hospital with COVID-19 patients, it’s important to consider the hypothesis testing and confidence interval with that study. A CI of 95% for this example would be better than a CI of 90%, because it’s important to have a true mean of the temperatures of the sample collected. This is because the CI is calculated by knowing the sample size, identifying the mean and standard deviation, and choosing the level of confidence interval (Ambrose, 2018). For my example, I chose 95% as the level of confidence interval.

It’s important to understand analytical quantitative research which involves hypothesis testing and confidence intervals in order to generate valid results from the samples for populations that are researched (El-Masri, 2016), especially for health care so that positive outcomes can be formed to improve patient care.

References

Ambrose, J. (2018). Clinical inquiry and hypothesis testing. Applied Statistics for Health Care. Retrieved from https://lc.gcumedia.com/hlt362v/applied-statistics-for-health-care/v1.1/#/chapter/3

El-Masri, M.M. (2016, June 1). Statistical versus clinical significance in nursing research. Canadian Journal of Nursing Research, 48(2), 31-32. doi: https://doi.org/10.1177/0844562116677895

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.