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An explanation of confidence intervals and their significance in statistical reasoning for the health sciences. It discusses the concept of confidence intervals, their range, and the advantages and disadvantages of using a systematic sampling method. The document also includes examples of confidence intervals for a sample of height data and their significance in determining population means.

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2022/2023

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Download Statistical Reasoning for Health Sciences: Confidence Intervals & Sampling Methods and more Lab Reports Mathematics in PDF only on Docsity! lOMoARcPSD|3013804 lOMoARcPSD|3013804 Week 7 Assignment: Lab XXXXXX MATH225N-10470: Statistical Reasoning for the Health Sciences XXXXXXX lOMoARcPSD|3013804 The two articles listed below were sourced using the link provided by the Chamberlain Library. First Article: Confidence Intervals, Part 1 Second Article: Confidence Intervals, Part 2 A confidence interval (CI) is the range of values thought to encompass the population value under study (El-Masri, 2012). This indicates that the true mean of the population is within the lower and higher boundaries of the confidence interval (CI) if a sample of data were to be taken, plotted on a table or graph, averaged, and the CI determined. The range of confidence can be 90%, 95%, or 99%. If the CI is large, such as the 90% CI, this may indicate that insufficient data were collected or that you are not as certain that the sample of data you have is truly representative of the mean. Since there is less room for mistakes when the CI is narrow, it is more accurately able to represent the population mean because it is so near to the sample set's actual mean value. It is more typical to utilize 95% CI in the health sciences. Other studies choose to calculate its statistical significance using the mean of two CIs. As a result, rather than focusing only on two distinct confidence intervals and their boundaries, they would take the mean of two CI; if the CI ranges overlap, the difference in the mean value is not statistically significant. However, the mean value is statistically significant if there is no overlap. Sampling Method Used The systematic approach of sampling was employed for this study. The participants' height data were determined using this procedure. Advantages lOMoARcPSD|3013804 The true mean of the measured heights has a 95% confidence interval, and according to the spreadsheet above, the lower limit is 66.979573 inches, and the upper limit is 69.420427 inches. The genuine mean of the 20 heights falls between 66.979573 inches and 69.420427 inches, and I can be 95% positive for this. In other words, the heights of the 20 individuals fall inside the range for 95% of them. lOMoARcPSD|3013804 The 95% CI's margin of error is 1.22, while the 99% CI's is 1.67. Contrary to logic, the margin of error appears to be greater in the 99% confidence interval. But in order to achieve 99% confidence, the CI range simply had to be expanded to accommodate additional heights. The CI values in 95% and 99% are not that far out from one another, though, due to my tiny sample size and the narrow range of height variations. lOMoARcPSD|3013804 References El-Masri, M. (2012). Coonfidence intervals: part 1. Canadian Nurse. 108(2). 8. https://web-b- ebscohostcom.chamberlainuniversity.idm.oclc.org/ehost/pdfviewer/pdfviewer? vid=3&sid=bdee4f5c-ce36-4b26-8400-70337d1b0dd9%40sessionmgr102