For grading purposes, this particular discussion posting area runs from Sunday Feb 7 through Sunday Feb 14, inclusively.
We explore inferential statistics this Week. This includes estimation ( confidence intervals ), a confidence interval for a mean, and a confidence interval for a proportion. We explore concepts such as the concept of a point estimate and the concept of a margin of error for a confidence interval. We explore concepts such as “confidence level” as well.
Please don’t forget to use an “outside” resource as part of the content and documentation for your first Post – the Post which is due on or before Wednesday of the Week – the Post where you make the most major contribution to the Weekly discussion posting area and attempt to address the discussion prompts / cues for the Week. It could possibly include a web site that you discovered on the internet at large, so long as the web site is relevant and substantial and does not violate the Chamberlain University policy for prohibited web sites, and so forth. It could possibly include references / resources that you discover through making use of the online Chamberlain University Library ( please click Resources along the left and then click Library to discover the link to the Chamberlain University online Library ) .
Check out the link below for some information about confidence intervals, the so-called margin of error, critical value( s ), and when to use t Distributions rather than normal distributions when finding a confidence interval under certain circumstances.
Link (Links to an external site.)Links to an external site.
This is one kind of an example of using an “outside” source / resource to add to what is revealed in our Weekly Lesson in Modules and in our Weekly text book reading.
Please don’t forget to look over the Graded Discussion Posting Rubric each Week to be certain that you are meeting all of the Frequency requirements as well as all of the Quality requirements for graded discussion posting each Week.
Hi Friends and Greetings !!
I tried another experiment with confidence intervals.
I calculated 4 95% confidence intervals all using the same sample mean of 65.8857 inches and the same population standard deviation of 3.5998 inches.
The only difference between the 4 95% confidence intervals is that I based the calculations of the confidence interval endpoints ( left endpoint and right endpoint ) on 4 different sample sizes of n = 35 and then n = 70 and then n = 105 and then n = 140 .
The 4 ( respective ) margins of error were 1.19 inches 0.84 inches 0.69 inches 0.60 inches
If this is not a coincidence – if the confidence interval for one population mean that we study and learn about in this course always behaves according to this trend / pattern – how can you put this trend / pattern into words ??
That is, all other things being equal ( the same or “fixed” ) then what happens to the margin of error as the sample size is increased ??
Another way of thinking about this is – if you use a larger sample size you are incorporating “more information” into the analysis – so what is the “reward” for doing that in this case ??
The n = 35 spread sheet is attached to this Post and the spread sheets for ( respectively ) n = 70 and then n = 105 and then n = 140 are attached to 3 further Posts just below here.
Thanks Friends and please see attached ( see the tab along the bottom for the z confidence interval – sample size larger than 30 – the left most tab along the bottom of the spread sheet )
Be sure to focus on just the 95% confidence interval and its margin of error in each of the 4 spread sheets
Thanks Friends and Very Best Wishes and Good Luck during this Week 6 !!
This Week is a busy one because we have to complete the Week 6 Knewton Quiz and also get off to a great start on the Week 7 lab turn in assignment in the SAME Week !!
Good Luck and THANK YOU so much for your hard work !!
Hi Elaine and Barb ! Greetings and thanks for your hard work !!
This Week 6 our confidence intervals are
( point estimate – margin of error , point estimate + margin of error )
which by the way means that the entire width / length of the confidence interval is two times the margin of error.
Also the midpoint of the confidence interval is the point estimate here in Week 6 .
Meaning that if we add the confidence interval endpoints together and divide by two, we get the point estimate back.
The point estimate for the confidence interval in the mean context is the sample mean xbar (frac{ }{X})
The point estimate for the confidence interval in the proportion context is the sample proportion phat
It is important to note that within Knewton sometimes they use the symbol p’ for the sample proportion rather than the symbol phat
The formula for the margin of error contains several elements / pieces / ingredients that don’t change no matter what confidence level is used to calculate the confidence interval ( to calculate the confidence interval endpoints ) .
The only piece / element / ingredient in the formula for the margin of error that changes with different confidence levels is the critical value.
In some cases this Week 6 we are talking about a critical z value here and in some cases this Week 6 we are talking about a critical t value here.
But focusing on the cases where we use a critical z value during this Week 6 , the critical z value changes from 1.645 to 1.96 to 2.575 as the confidence level goes from 90% to 95% to 99%
So in calculating the margin of error for the confidence interval for each of these confidence levels, we multiply some fixed quantity times an ever increasing number ( ever increasing critical z value ) as the confidence level goes higher and higher.
That is why “all other things being equal,” the margin of error increases with increasing confidence level.
All this stuff mentioned here recently would be a really good answer to one of the important questions near the end of the Week 7 lab assignment next Week 7 !!
Thanks Barb and Elaine and Everyone have a Terrific day and a Fantastic Week 6 !!
Dear Professor and Classmates,
One of the things I track is door to electrocardiogram time (D2EKGT) and door to balloon time (D2BT) for ST elevation myocardial infarction (STEMI) patients. EKG, taken from the German spelling, is often used because ECG can be confused with echocardiograms. Studies have shown that getting the EKG is done in 10 minutes or less translates to quicker reperfusion times. One such study was done in the National Taiwan University Hospital in 2014 (Lee et al., 2019) and showed that the D2EKGT was the most critical interval of delay in getting patients to the cath lab and reperfused. Therefore, it is something my department keeps a watchful eye on with every STEMI.
In that study, they created an EKG station in the triage area so they wouldn’t have to transport the patients to another area to do an EKG. Patients who arrived after the new EKG station was created were the intervention group, and their D2EKG and D2B times were compared to a somewhat equal number of patients that came to the emergency department in the months before the EKG station was put in the triage area; those were the control group (Lee et al., 2019). The required sample size was 62 patients in each group (intervention and control) with 80% power and a type 1 error of 0.05 (Lee et al., 2019). This isn’t covered until Chapter 9 in our text, and since I found Chapter 8 confounding enough, I will worry about what that means later. However, the following is something easy to understand. One example in the study compared the D2EGKT of walk-in patients and how it affected the D2BT before and after the change in the triage area (Lee et al., 2019): 93.3% of walk-in patients got their EKGs in <10 mins after the change vs 79.8% before the EKG station was set up in the triage area. This translated to 91.1% of those patients having a D2BT <90 mins vs 76.2% before (Lee et al., 2019).
If I wanted to reproduce that in my hospital, I think I’d have to apply the confidence interval for the population mean. As per this week’s online lesson (Chamberlain University, 2021), interpreting confidence interval is based on repeated sampling. A 95% confidence interval means that if I had 100 different samples each with a different mean, 95 would contain the population value and 5 would not. I hope my understanding is correct that they mean sets of 100 values, so you can get varying means. For the 93.3% of walk-in patients who got their EKG in <10 minutes in the Taiwan study, to replicate that with 95% confidence interval, and assuming 100 patients, the calculated lower limit would be 89 patients and the upper limit would be 98 patients. The excel calculations show fractions, but as per our lesson, we cannot go below a minimum and we cannot sample a fraction of a person, so we round up, not down (Chamberlain University, 2021).
Lowering the confidence interval to 90% changes the lower and upper limits to 90 and 97 respectively. Raising the confidence interval to 99% changes the lower and upper limits to 87 and 99. The CI of 90% gives us a narrower interval range but we’d rather have the higher confidence of 95%, right? That is the “trade off” described on page 340 of our text and demonstrated by the curve Figure 8.6 (Holmes et al., 2018). Increasing the CI to 99% makes the interval even wider.
So, if my understanding is correct, and I wanted to replicate the success seen in Taiwan with 95% confidence, I’d need 89 to 98 patients of 100 to get their D2EKG times to <10 minutes. Is that correct?
Thanks,
Elaine
Chamberlain University. (2021). MATH225. Week 6: Confidence intervals (Online lesson). Downers Grove, IL: Adtalem.
Holmes, A., Illowsky, B., & Dean, S. (2018). Introductory business statistics. OpenStax.
Lee, C., Meng, S., Lee, M., Chen, H., Wang, C., Wang, H., Liao, M., Hsieh, M., Huang, Y., Huang, E., Wu, C. (2019). The impact of door-to-electrocardiogram time on door-to-balloon time after achieving the guideline-recommended target rate. PLoS ONE 14 (9), 1-14. https://chamberlainuniversity.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=138516728&site=eds-live&scope=siteLinks to an external site.
