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.
In my workplace, we look at falls at least quarterly and annually. If I wanted to know the mean of the falls for
the year, I would get the number of falls each month and determine the mean from the 12 months for the year.
This would give me an example of the mean number of falls for the facility only for that year. I could use this
sample for overall falls that have taken place over years since the facility opened. Based on the data collected
from the number of falls, the CI of 95%, the mean, and standard deviation would be used to estimate the mean
of the overall falls.
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.
Sample Solution