Answer for HLT 362 Evaluate and provide examples of how hypothesis testing and confidence intervals are used together in health care research Re: Topic 3 DQ 2

Hypothesis testing and confidence intervals are two important statistical tools that are commonly used together in health care research. “The hypothesis is a prediction of what will happen between the two variables” (June Helbig & Jayme Ambrose, 2022). “The confidence interval (CI) is an interval estimate for the mean” (June Helbig & Jayme Ambrose, 2022). “It is a range of values that are set close to the mean either in a positive or negative direction” (June Helbig & Jayme Ambrose, 2022). “For the null to be rejected, 95% of the values need to set close to the mean” (June Helbig & Jayme Ambrose, 2022). While hypothesis testing helps determine if an observed effect is statistically significant, confidence intervals provide a range of values in which the true population parameter likely falls. A study might test the hypothesis that a new rehabilitation technique reduces recovery time after surgery. Upon rejecting the null hypothesis, the study might report a 95% CI for the average reduction in recovery days. In a hospital setting, a CI between 3 to 5 days confirms technique effectiveness and expected outcomes. This dual approach offers both statistical and practical significance, guiding clinicians in setting realistic expectations and improving patient care.

References:

June Helbig & Jayme Ambrose. (2022). Applied Statistics for Health Care. Grand Canyon University (Ed.). (2022). Applied statistics for health care (2nd ed.).