Hello Professor and Class.
For this article, I chose an article by The Wisconsin Department of Health Services explaining confidence interval studies. This study does an excellent job of putting these weeks’ lessons into simple laymen terms that helped me understand the concept.
“In 2005 the estimated percentage of current smokers among Wisconsin adults was 20.7%, with a confidence interval of +/- 1.1%. The estimated population of current smokers was 850,900.
First, calculate the range of the population confidence interval:
R = (1.1/20.7)*850,900 = 45,217 (or 45,200 rounded to the nearest 100)
Then calculate the confidence interval by applying the range to the estimated population:
CI = 850,900 +/- 45,200
In other words, there is a 95% probability that in 2005 the true number of adult smokers in Wisconsin fell within the range of 805,700 – 896,100 people.” (2023)
By using confidence intervals this study demonstrates how confidence intervals can be used in this case for behavioral risk factors. So instead of asking every resident of the state they can take a sample size and work out the probability. It also shows how factors affect the size of the confidence interval. One is the desired confidence meaning a higher percentage such as 99% would lead to a wider interval. The second is the sample size used for the estimate the larger the size the smaller the confidence interval will be.
References
Behavioral risk factor survey module: Confidence intervals around sample estimates. Wisconsin Department of Health Services. (2023, January 5). https://www.dhs.wisconsin.gov/wish/brfs/confidence-intervals.htm#:~:text=For%20example%2C%20in%202005%20the,(20.7%25%20%C2%B1%201.1%25).