Steps to Complete the Week 6 Lab Find this article in theChamberlain Library. Once you click each link, you will be loggedinto the Library and then click on "PDF Full Text". First Article:Confidence Intervals, ( I copied and pasted both articles at thebottom of this question).

1. Consider the use of confidence intervals in health scienceswith these articles as inspiration and insights.

2. Describe how you could use confidence intervals to help makea decision or solve a problem in your current job, a clinicalrotation, or life situation. Include these elements: Description ofthe decision or problem

3. How the interval would impact the decision and what level ofconfidence would be most appropriate and why What data would needto be collected and one such method of how such data could ideallybe collected

Articles to use:

Confidence interval: The range of values, consistent with thedata, that is believed to encompass the actual or “true” populationvalue Source: Lang, T.A., & Secic, M. (2006). How to ReportStatistics in Medicine. (2nd ed.). Philadelphia: American Collegeof Physicians

Confidence interval: The range of values, consistent with thedata, that is believed to encompass the actual or "true" populationvalue Source: Lang, T.A., & Secic, M. (2006). How to ReportStatistics in Medicine. (2nd ed.). Philadelphia: American Collegeof Physicians

Hope this information helps:

1. Consider the use of confidence intervals in health scienceswith these articles as inspiration and insights.
2. Describe how you could use confidence intervals to help make adecision or solve a problem in your current job, a clinicalrotation, or life situation. Include these elements:
   1. Description of the decision or problem
   2. How the interval would impact the decision and what level ofconfidence would be most appropriate and why
   3. What data would need to be collected and one such method of howsuch data could ideally be collected

These are the articles provided for the homework:

To draw conclusions about a study population, researchers usesamples that they assume truly represent the population. Theconfidence interval (CI) is among the most reliable indicators ofthe soundness of their assumption. A CI is the range of valueswithin which the population value being studied is believed tofall. CIs are reported in the results section of published researchand are often calculated either for mean or proportion data(calculation details are beyond the scope of this article). A 95%CI, which is the most common level used (others are 90% and 99%),means that if researchers were to sample numerous times from thesame population and calculate a range of estimates for thesesamples, 95% of the intervals within the lower and upper limits ofthis range will include the population value. To illustrate the 95%CI of a mean value, say that a sample of patients with hypertensionhas a mean blood pressure of 120 mmHg and that the 95% CI for thismean was calculated to range from 110 to 130 mmHg. This might bereported as: mean 120 mmHg, 95% CI 110-130 mmHg. It indicates thatif other samples from the same population of patients weregenerated and intervals for the mean blood pressure of thesesamples were estimated, 95% of the intervals between the lowerlimit of 110 mmHg and the upper limit of 130 mmHg would include thetrue mean blood pressure of the population. Notice that the widthof the CI range is a very important indicator of how reliably thesample value represents the population in question. If the CI isnarrow, as it is in our example of 110-130 mmHg, then the upper andlower limits of the CI will be very close to the mean value of thesample. This sample mean value is probably a more reliable estimateof the true mean value of the population than a sample mean valuewith a wider CI of, for example, 110-210 mmHg. With such a wide CI,the population mean could be as high as 210 mmHg, which is far fromthe sample mean of 120 mmHg. In fact, a very wide CI in a studyshould be a red flag: it indicates that more data should have beencollected before any serious conclusions were drawn about thepopulation. Remember, the narrower the CI, the more likely it isthat the sample value represents the population value.

Part 1, which appeared in the February 2012 issue, introducedthe concept of confidence intervals (CIs) for mean values. Thisarticle explains how to compare the CIs of two mean scores to drawa conclusion about whether or not they are statistically different.Two mean scores are said to be statistically different if theirrespective CIs do not overlap. Overlap of the CIs suggests that thescores may represent the same "true" population value; in otherwords, the true difference in the mean scores may be equivalent tozero. Some researchers choose to provide the CI for the differenceof two mean scores instead of providing a separate CI for each ofthe mean scores. In that case, the difference in the mean scores issaid to be statistically significant if its CI does not includezero (e.g., if the lower limit is 10 and the upper limit is 30). Ifthe CI includes zero (e.g., if the lower limit is -10 and the upperlimit is 30), we conclude that the observed difference is notstatistically significant. To illustrate this point, let's say thatwe want to compare the mean blood pressure (BP) of exercising andsedentary patients. The mean BP is 120 mmHg (95% CI 110-130 mmHg)for the exercising group and 140 mmHg (95% CI 120-160 mmHg) for thenon-exercising group. We notice that the mean BP values of the twogroups differ by 20 mmHg, and we want to determine whether thisdifference is statistically significant. Notice that the range ofvalues between 120 and 130 mmHg falls within the CIs for bothgroups (i.e., the CIs overlap). Thus, we conclude that the 20 mmHgdifference between the mean BP values is not statisticallysignificant. Now, say that the mean BP is 120 mmHg (95% CI 110-130mmHg) for the exercising group and 140 mmHg (95% CI 136-144 mmHg)for the sedentary group. In this case, the two CIs do not overlap:none of the values within the first CI fall within the range ofvalues of the second CI. Thus, we conclude that the mean BPdifference of 20 mmHg is statistically significant. Remember, wecan use either the CIs of two mean scores or the CI of theirdifference to draw conclusions about whether or not the observeddifference between the scores is statistically significant.