MATH 225N Week 6 Discussion: Confidence Interval
Initial Post Instructions
Thinking of the many variables tracked by hospitals and doctors’ offices, confidence intervals
could … created for population parameters (such as means or proportions) that were calculated
from many of them.
Choose a topic of study that is tracked (or you would like to see tracked) from your place of
work. Discuss the variable and parameter (mean or proportion) you chose, and explain why you
would these to create an interval that captures the true value of the parameter of patients with
95% confidence.
Consider the following:
How would changing the confidence interval to 90% or 99% affect the study? Which of these
values (90%, 95%, or 99%) would best suit confidence level according to type of study chosen?
How might the study findings … presented to those in charge in an attempt to affect change at
the workplace?
NB: 2 Answers Displayed
, Confidence Intervals
In everyday terms, a confidence interval is the range of values around a sample statistic (such as
mean or proportion) within which clinicians can expect to get the same results if they repeat the
study protocol or intervention, including measuring the same outcomes the same ways. As you
ask yourself, "Will I get the same results if I use this research?", you must address the precision
of study findings, which is determined by the Confidence Interval. If the CI around the sample
statistic is narrow, you can be confident you will get close to the same results if you implement
the same research in your practice.
Consider the following example. Suppose that you did a systematic review of studies on the
effect of tai chi exercise on sleep quality, and you found that tai chi affected sleep quality in
older people. If, according to your study, you found the lower boundary of the CI to be .49, the
study statistic to be 0.87, and the upper boundary to be 1.25, this would mean that each end limit
is 0.38 from the sample statistic, which is a relatively narrow CI.
(UB + LB)/2 = Statistic [(1.25 + .49)/2 = .87]
Keep in mind that a mean difference of 0 indicates there is no difference; this CI does not contain
0. Therefore, the sample statistic is statistically significant and unlikely to occur by chance.
Because this was a systematic review, and tai chi exercise has been established from the studies
you assessed as helping people sleep, based on the sample statistics and the CI, clinicians could
now use your study and confidently include tai chi exercises among possible recommendations
for patients who have difficulty sleeping.
Now you can apply your knowledge of CIs to create your own studies and make wise decisions
about whether to base your patient care on a particular research finding.
Initial Post Instructions
Thinking of the many variables tracked by hospitals and doctors’ offices, confidence intervals
could … created for population parameters (such as means or proportions) that were calculated
from many of them.
Choose a topic of study that is tracked (or you would like to see tracked) from your place of
work. Discuss the variable and parameter (mean or proportion) you chose, and explain why you
would these to create an interval that captures the true value of the parameter of patients with
95% confidence.
Consider the following:
How would changing the confidence interval to 90% or 99% affect the study? Which of these
values (90%, 95%, or 99%) would best suit confidence level according to type of study chosen?
How might the study findings … presented to those in charge in an attempt to affect change at
the workplace?
NB: 2 Answers Displayed
, Confidence Intervals
In everyday terms, a confidence interval is the range of values around a sample statistic (such as
mean or proportion) within which clinicians can expect to get the same results if they repeat the
study protocol or intervention, including measuring the same outcomes the same ways. As you
ask yourself, "Will I get the same results if I use this research?", you must address the precision
of study findings, which is determined by the Confidence Interval. If the CI around the sample
statistic is narrow, you can be confident you will get close to the same results if you implement
the same research in your practice.
Consider the following example. Suppose that you did a systematic review of studies on the
effect of tai chi exercise on sleep quality, and you found that tai chi affected sleep quality in
older people. If, according to your study, you found the lower boundary of the CI to be .49, the
study statistic to be 0.87, and the upper boundary to be 1.25, this would mean that each end limit
is 0.38 from the sample statistic, which is a relatively narrow CI.
(UB + LB)/2 = Statistic [(1.25 + .49)/2 = .87]
Keep in mind that a mean difference of 0 indicates there is no difference; this CI does not contain
0. Therefore, the sample statistic is statistically significant and unlikely to occur by chance.
Because this was a systematic review, and tai chi exercise has been established from the studies
you assessed as helping people sleep, based on the sample statistics and the CI, clinicians could
now use your study and confidently include tai chi exercises among possible recommendations
for patients who have difficulty sleeping.
Now you can apply your knowledge of CIs to create your own studies and make wise decisions
about whether to base your patient care on a particular research finding.
