Confidence Interval

Question Description

You have been assigned a topic according to the first letter of your last name. Please identify the topic assigned to you below. For each topic, find a health science example of it in a published research study or news article. Explain your assigned concept and relate how your topic is used in the example. Initial Question is on the topic of Confidence Interval.

Your initial response to the Discussion topic should be a minimum of 200 words. You should also provide at least two responses to your classmates that should be a minimum of 100 words. In your peer replies, you are encouraged to challenge responses to promote critical thinking on all sides of a discussion.

Classmate Post #1

This article that I found talks about conflict between clinical importance and statistical significance, this is an important problem in medical research. Although clinical importance is best described by asking for the effect size or how much, statistical significance can only suggest whether there is any difference. One way to combine statistical significance and effect sizes is to report confidence intervals. Confidence intervals could help avoid such erroneous interpretation by showing the effect size explicitly. The classic research questions in orthopedics are whether a group of patients improved, for example if they had less pain and or better function, after a particular treatment, or whether a treated group of patients improved compared with an untreated group. Strictly speaking a 95% confidence interval means that if we were to take 100 different samples and compute a 95% confidence interval for each sample, then approximately 95 of the 100 confidence intervals will contain the true mean value (μ).

Reference: Vavken, P. (2009). The Use of Confidence Intervals in Reporting Ortghopaedic Research Finding. Clinical Orthopaedics and Related Research. Retrieved from

Classmate Post #2

Statistical significance is basically a way of proving that a certain statistic is reliable mathematically. It is the difference in conversion rates between a given variation and the baseline is not due to a random chance (Statistical Significance, 2018). If an experiment in not caused by chance then it is considered statistically significant. Experiments need statistical significance before you can make a decision. As long as you have a 95% chance that the results are not based on randomness, then it has statistical significance. Statistical significance is most commonly used in statistical hypothesis testing.

Statistical Significance. (2018). Optipedia. Optimizely. Retrieved from

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