Why Are Confidence Lengths Important?

Confidence intervals are useful in helping to determine clinical significance due to the fact that they address collected data, such as a range of values that are contained in a sample population. After those results are gathered, then they are evaluated in order to help decide if they are clinically significant or not. According to Fethney (2010), “Confidence intervals are one way for researchers to help decide if a particular statistical result may be of relevance in practice”(para. 1, p. 93). Confidence intervals are of practical value and provide clinical significance due to the fact that they provide a good approximation of the possible results that will be collected after initiating the interventions in daily practice. In the lesson for this week it is stated that a confidence interval is “how close the mean or median falls to the true value for the population” (CCN,

What I understand this to mean, is that the data has self-assurance that the values are appropriate when we repeat a test several times. The value that is given is a representation of a range in values that demonstrates confidence at 90, 95, or 99% that it is correct. The most commonly used is 95%. The reason why this is significant is due to the fact that it demonstrates practicality and relevance in that the estimates are most likely the true and valid results.

With regards to clinical significance and statistical significance, the way that I understand it is that clinical significance is the total effect of the treatment in tangible terms, whereas statistical significance comes from the number that was a direct result of an experiment or trial. What varies between the two is, for me, sometimes difficult to understand, let alone to explain in many ways. Experimental trials demonstrate