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Hypothesis tests and confidence intervals work by focusing on concepts and graphs rather than equations and numbers. A confidence interval is a range of values that is likely to contain an unknown population parameter. If you draw a random sample many times, a certain percentage of the confidence intervals will contain the population mean. This percentage is the confidence level. An example of whether or not acupuncture and massage are effective in treating back pain can be used. The null hypothesis Ho would be that there is no positive effect; Ho: mean pain levels for acupuncture and massage are remain the same, and if there is a difference it is from an error. The alternative hypothesis HA is used to prove there is a change in the back pain from using acupuncture and massage. The point estimate is used to show the difference between the groups evaluated for the research. “Confidence intervals can be calculated for most summary measures such as means, proportions, and differences in means, and in most cases can be easily calculated by knowing the values of the summary measure, the variability in the summary measure and the sample size.” (Thomas,2019 pg 104, para 2) Because it is impossible to have 100% certainty in the range, a confidence level is used of 95%. For the research in lower back pain, a confidence interval can be used for the mean level in difference in pain levels.
“Confidence intervals can be calculated for most summary measures such as means, proportions, and differences in means, and in most cases can be easily calculated by knowing the values of the summary measure, the variability in the summary measure and the sample size.” (Thomas, 2019 pg 105, para 2)
An example of this used at work would be quality measures. In every patients EMR we have a quality measure tab that must be checked every time anyone is in the chart. This alerts us to potential measures that need to be verified to maintain maximum quality measures. Some patients have BMI highlighted indicating we need to evaluate height, weight, and education on diet and exercise. Another may be pap smear; this could be needed because the patient doesn’t have a pap smear order/result on record so the nurse would need to obtain information on when and where the patient had their last pap smear to obtain the result to satisfy the measure.
Elaine Thomas PhD MSc BSc.An introduction to medical statistics for health care professionals:
Hypothesis tests and estimation.Retrieved
from:https://onlinelibrary.wiley.com/doi/pdf/10.1002/ms…
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