Hypothesis Testing and Confidence Interval in Health Care Research

Hypothesis Testing and Confidence Interval
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Hypothesis Testing and Confidence Interval
Confidence interval is a range of possible values likely to capture an unknown parameter based on a certain degree of probability (confidence) (Hazra, 2017). The percentage Confidence level is equal to minus α, where alpha is typically called the accepted error or significance level, which is often equal to 0.05. However, the value might vary depending on the situation. Thus, the most likely example of CI is 95%. It means that if sampling was done several times and the confidence interval for a specific parameter like regression coefficient calculated, then it would be expected that 95% of the intervals to capture the actual population.
On the other hand, hypothesis testing allows the researcher to conclude the possibility that a given hypothesis is using sample data from the required population (Shreffler & Huecker, 2021). A hypothe...