Question

Healthcare administration leaders are asked to make evidence-based decisions on a daily basis. Sometimes, these decisions involve high levels of uncertainty, as you have examined previously. Other times, there are data upon which evidence-based analysis might be conducted. This week, you will be asked to think of scenarios where building and interpreting confidence intervals (CIs) would be useful for healthcare administration leaders to conduct a two-sided hypothesis test using fictitious data. For example, Ralph is a healthcare administration leader who is interested in evaluating whether the mean patient satisfaction scores for his hospital are significantly different from 87 at the .05 level. He gathers a sample of 100 observations and finds that the sample mean is 83 and the standard deviation is 5. Using a t-distribution, he generates a two-sided confidence interval (CI) of 83 +/- 1.984217 *5/sqrt(100). The 95% CI is then (82.007, 83.992). If repeated intervals were conducted identically, 95% should contain the population mean. The two-sided hypothesis test can be formulated and tested just with this interval. Ho: Mu = 87, Ha: Mu<>87. Alpha = .05. If he assumes normality and that population standard deviation is unknown, he selects the t-distribution. After constructing a 95% CI, he notes that 87 is not in the interval, so he can reject the null hypothesis that the mean satisfaction rates are 87. In fact, he has an evidence-based analysis to suggest that the mean satisfaction rates are not equal to (less than) 87.

Consider how a CI might be used to support hypothesis testing in a healthcare scenario. Post a description of a healthcare scenario where a CI might be used, and then complete a fictitious two-sided hypothesis test using a CI and fictitious data.

Answer 1

ANSWER:

Healthcare administration leaders are asked to make evidence-based decisions :

Required information is given by ,

mu = 87 ,

n=100

x bar =83 , standard deviation = 5.

alpha=0.05 .

Calculated:

Consider how a CI might be used to support hypothesis testing in a healthcare scenario :

We have to obtained the CI might be used to support hypothesis testing in a healthcare scenario is ,

Here,

A confidence interval  is a scope of qualities that is probably going to contain an unknown population parameters..we use confidence intervals to bound the mean or standard deviation,but it can likewise get them for regression coefficients, proportions,rates of occurence and for the contrast between population..but there are normal misguided judgment between P value and confidence interval (CI).. Theory test helps find out examining mistakes between an example and the whole populace.. Theory testing significant method in social insurance statistics..it assesses two mutually statement about a populace to figure out which proclamation is best upheld by the sample data.

In this solution two-sided hypothesis test obtained and tested just with this interval..He selects t- distribution if he can n't assume standard deviation..here confidence interval (CI) used him to constructing a 95% confidence interval ,he notes 87 is n't in the interval,so he rejected null hypothesis..he got a evidence--based analysis..so as I said before confidence interval useful to support hypothesis testing in health care to find the population parameters, patient satisfaction scores etc.

Therefore ,

We rejected null hypothesis (H_0).