Confidence interval put values in green cells; output or answers in

1. Confidence IntervalPut values in GREEN cells; output or
answers in YELLOW cellsEnter input in blue cells ; Look for
answers in yellow cellst or z Confidence Interval for
µConfidence Interval for p ProportionsConfidence
Level0.990Enter decimalConfidence Level0.950Enter
decimaln27n329Mean17.3185Number of
Successes141StDev3.4029pop stdevnoEnter yes if population
stdev knownEnter No if population stdev is
unknownSE0.654888Sample
Proportion0.428571t2.779SE0.027283Margin of
Error1.819935z1.960Lower Limit15.498565Margin of
Error0.053475Upper Limit19.138435Lower
Limit0.375096Upper Limit0.482046
sample mean & standard deviatioPut values in blue cells; output
or answers in YELLOW cellsEnter values starting from B5
cellData18.4Mean17.318516.1Sample Standard
Deviation3.402919.516.512.517.213.817.919.19.823.818.719.11
519.21711.515.722.523.719.917.61517.820.714.215.4
Minimum Sample SizeEnter input in blue cells ; Look for
answers in yellow cellsMinimum Sample Size μ for population
meanMinimum Sample Size p for ProportionConfidence
Level0.950Enter decimalConfidence Level0.920Enter
decimalStDev10Sample Proportion0.5If sample proportion
unknown enter 0.5Error3Error0.03Write percentage as
decimalz-Value1.960z-Value1.751Minimum Sample
Size43Minimum Sample Size852
EMPIRICAL RULEEmpirical Rule using standard error for
CONFIDENCE INTERVALANSWEREmpirical Rule68-95-
99.7mean0.43Lower numberUpper number standard
deviation068%0.370.49Standard
error0.0695%0.310.5599.70%0.250.61
Hello, Sylvain. What I wanna do is give you a brief overview
of what you have to do for your week seven Lab. So in the week

2. seven lab, the only spreadsheet we're going to really need is
your week six spreadsheet. So if you go to Modules and under
week six and got the lesson here shall weeks, Week six
spreadsheet. I've already downloaded it, so it looks like this. So
this is the spreadsheet you should have downloaded for the
lab. So I will download that. Another thing that I would
download is the week seven Lab. So that looks like this. Now
remember these lecture notes are for you to write all over
them. Make any little documentation that you would like to help
you do your lab. Ok. So in the week seven lab, you're, the only
spreadsheet you need is the week six spreadsheet, but you do
need your week five lab data. So go ahead and take a moment to
pull that. That should be the ten heights that your
instructor gave you and then the ten heights that you
gathered. Ok. So to get, I talk about how to get the weeks, six
spreadsheets. So you have that. Now in order to kind of give an
example of what you're going to do in your lab. I want to go
back and look at our data from lab five. Now remember the
scenario for lab five. I'm a principal of a high school. I walk
down the senior map hallway and I picked one class in one class
had ten students in it. And I pooled their midterm exam math
scores. And they're listed here. If you remember from lab from
last week that our mean, I'm just going to write it here. Feel
free to fill in on your sheet. Our mean was a 76.9. Our standard
deviation was 11.3964. And if remember our score that we were
comparing was an 85. So I'm gonna write those down. Okay? So
what I wanna do is I want to find a 95% confidence interval
for the true mean midterm average of all the people in the class
spraying it all. And then even trying to branch out further if we
could to all the people in that or see years or whatever, what
would the population we're trying to represent. So if you open
up your week six spreadsheet, it's asking for competence
level. And so our first one is 95. N is how many pieces of data
we have. We only have ten. Are mean was 76.9, our standard
deviation was 11.396 for population standard deviation, our
answer is no, we don't know, we didn't have a

3. population. They're asking if this standard deviation is a
population standard deviation or not. And it was not because
we've pulled a sample. Okay. You would only type yes, here if
you've actually pulled an entire population. Okay? And so then
it gives us some great information here in yellow. But the one
thing you're going to take a look at are these the margin of
error, you're lower and your upper limit. So I'm going to take a
screenshot because that's the first thing that's asking for. Take a
screenshot or Dina and you feel free to do the same so that you
have it. And then I'll even, and then you can print these out and
look at them while you're doing it for lab. Let me make it very
small. So it, since he got up into space. Okay. So there's my
95% confidence at all. Now, give a practical interpretation of
what this means. Well, what this means is that I can write, I am
95% confident. I am 95% confident that the true average of the
mass mid-term exam is between 68.785.1 k. I am 95% confident
that the true average, remember we only pull ten people. But if I
were, if I wanted that to represent the entire average of the
midterm exam of everybody who took it. It's between a
68.785.1. I'm 95% sure that the average will be there. So what I
mean by that is I would have to verify I would have to go and
pull the midterm math exam of every single student who took it
in that senior year at that school and average it out. And what
I'm saying is a 95% sure that that average will fall between
60.785.1. A lot of students say, oh, I'm 95% confident that the
average of my sample, now, you know the average of your
sample, the average of your sample with 76.9. So don't, when
you're making a practical interpretation, you're not saying
something about the sample. You're seeing something about the
true mean of the population. If that makes sense. So you're
basing it off of the sample that you have. Okay? Then what
you're gonna do is you're going to do a 99% confidence
interval. So all you have to do is go back to our spreadsheet and
I, and when its height in, in blue, that I'm changing the
confidence level from 0.952.99. So let's change this to
0.99. Then I'm going to take a screenshot in your answers

4. should match mine right now. We're doing this together for the
midterm math example. Okay? So here's my screenshot. Now
this is for a 99% confidence interval. So what is the practical
interpretation of that? Again, let's write this out. I am 99%
confident that the true average of the midterm exam is between
65.288.6. So 60 by 0.288.6. And I'm getting that from the lower
and the upper limit of my confidence interval. Now, want you to
do is I want you to look at the margin of error. The margin of
error for being 99% confident was 11.7, and the margin of error
for being 95% confident was 8.15. What does that
mean? Explain what that even means. What would the margin
of error be larger or smaller? So in this case, and I want to tell
you the answer for years, but for this case, it would be
larger. And I want you to think about why that is. Look at the
confidence intervals themselves. If you come back up here for
the 95, mm, the 95 was between 68.785.1 and this is
65.288.6. It's kind of hard. You want to see if we can look at
them side-by-side even that would be great. But you should
notice that the interval for the 99% confidence is wider. It's a
wider interval. Why is that? Think about that. Why is it, why is
it bigger? Well, I want you to think about this. If you're 99%
confident, that means that you don't want to be wrong, right? I
mean, you never want to be wrong anytime. But 99% confidence
means that you're, you're, you're pretty sure, like you're
very, very sure that it's going to fall between 65.20.6. That the
more sure. How could you even me washer by opening up the
interval? Does that make sense? So let me demonstrate here,
maybe this will make more sense. Let's say I was like, I am sure
that the average amount of rain I'm going to get is two inches
and six inches of rain, I'm sure but 95%. Well, I don't want you
to be 95%. I want you to be 99%. All of you want me to be that
sure. I'm sure is between 015 Inches of rain. I don't know where
we're living but 0.15. so what I did is I've widened my interval
so that I could have the amount of inches of rain inside of my
interval. You widen it, you include more numbers. Therefore,
that makes you more confident. Okay? So that's what happened

5. here. So what we did just to recap, we took data from last week,
okay? And we looked at the mean, the score, and the standard
deviation, and we constructed a 9599% confidence interval. We
talked about what they mean in context of the problem. Okay?
We also looked at what happened to the interval itself as we
become more confident and feel free to play around with this a
little bit. What if you're 80% confident? What if you're 90%
confident? So look what happens to your margin as you do
that. Look what happens to the length of your interval when
you change your level of confidence. That's really great to bring
in to your lab. So hopefully that explains what we're gonna do
in your actual lab. So let's look at your actual lab. So what
you're going to be doing is you're going to first, I want you to
read articles about competence intervals. I would really like you
to see how they apply, especially in the health sciences. And
these articles will kind of inspire that thought. Okay? And then
what you're gonna do is you're going to, and I would love the
little summary. I would love a little summary starting off this
lab of what you learned from these articles. Then the next
step, using the data that you collected in week five. Now
remember in week five, you had ten different peoples height
plus the ten that you or your professor gave you. So you should
have 20 numbers. I want you to discuss the Gad Yair method
of collection was its systematic convenience. Cluster, cluster
stratified simple random. What are some false? I know you
highlighted this in week five, but now I want you to talk about
what are some faults with the type of data collection,
okay. What other types of data collections could you used
instead? And how might that affected your survey? So this right
here is the really important part. This is what I am trying to see
what you have learned, okay? So it's about telling me again
what type of method you chose. Telling me what faults come
with that method, some research might be involved. And then
telling me another type of method that you would've liked to try
if you could have and how that would affect your study. Okay.
Then you're going to tell me what the point estimate was, the

6. point estimates, your mean. So in our case when we're talking
about the midterm, whereas my lecture notes here again, this
right here, maybe I should write this down. The mean, the
76.9, that's your point estimate. This is what we're basing it off
of. Okay? So the point estimate is the mean. Okay? So give a
point estimate for the mean of the average height of all people
at the place of your work. If that's where you pull your sample
and start by putting the 20 heights you are working with into the
blue data. So we've done this already. You should already have
your data in and you know what your mean is in your sample
standard deviation. Then what you're gonna do is you're going
to construct a 95% confidence interval for the true mean height
of all the pupil, the place of your work, what is the
interval? And provide a screenshot which we did today. Then
you're going to give me a practical interpretation what this
means. So what you're explaining is your 95% confident that the
true mean height of all the people that you work with or the
population that you have is between this and this, okay? Then
you're gonna put, of course going to post a screenshot. Then
you're going to change your confidence levels. With 99%
confidence level, you're going to take a screenshot and provide
that as well. You're going to compare the margins of error. So
this is where you're going to talk about what happened to your
margin of error when we went from a 95 to 99% confidence
interval, what happened to your interval when he went from 95
to 99% confidence interval? There should be a good
paragraph explaining what happened, why it's happening, and
try to explain it in the context of the data and the lab. And that's
it. And then you're just going to save your document and
upload and that will submit your work. Please feel free to reach
out if you have any questions or concerns.
Lab 7 Lecture Notes
You will need your Week 5 Lab Data!!

7. 1. Go to Modules in the course room and click on Week 7
Lesson: Hypothesis Testing
2. Click on Week 7 Assignment: Lab
3. Download the Week 6
4. Let’s look at our data from Lab 5!
Data Set: Ten Grades on the Midterm Exam
50
68
74
77
80
86
86
80
78
90
Mean: ________ Our Score: _________
Standard Deviation: _________
5. Find a 95% confidence interval for the true mean Midterm
Average of all the people in the class. What is the interval?
[Provide a Screenshot].

8. 6. Give a practical interpretation of the 95% confidence
interval.
7. Find a 99% confidence interval for the true mean Midterm
Average of all the people in the class. What is the interval?
[Provide a Screenshot].
8. Give a practical interpretation of the 99% confidence
interval. Would the margin of error be larger or smaller for the
99% CI? Explain your reasoning.
Lab 7 Overview
J
LU

9. TERMINOLOGY 101
Confidence intervals: Part 2
MAHER M. EL-MASRI, RN, PhD, IS AN ASSOCIATE
PROFESSOR AND RESEARCH LEADERSHIP CHAIR
IN THE FACULTY OF NURSING, UNIVERSITY OF
WINDSOR, IN WINDSOR, ONT.
Confidence interval: The range of values, consistent with the
data, that is believed to encompass the actual or
"true" population value
Source: Lang, T.A., & Secic, M. (2006). How to Report
Statistics in Medicine. (2nd ed.). Philadelphia: American
College of Physicians
Part 1, which appeared in the February 2012
issue, introduced the concept of confidence
intervals (CIs) for mean values. This article
explains how to compare the CIs of two mean
scores to draw a conclusion about whether or
not they are statistically different. Two mean
scores are said to be statistically different if their
respective CIs do not overlap. Overlap of the CIs
suggests that the scores may represent the same
"true" population value; in other words, the true
difference in the mean scores may be equivalent
NurseONE resources
ON THIS TOPIC
EBSCO-MEDLINE FULL-TEXT ARTICLES
• Hildebrandt, M., Vervölgyi, E., & Bender, R. (2009).
Calculation of NNTs in RCTs with time-to-event

10. outcomes: A literature review. BMC Medical
Research Methodology, 9,21.
• Hildebrandt, M., Bender, R., Gehrmann, U.,
& Blettner, M. (2006). Calculating confidence
intervals for impact numbers. ß/MCMed/co/
Research Methodology, 6, 32.
• Altman, D. G. (1998). Confidence intervals forthe
number needed to treat. BMJ (Clinical Research
Ed.), 317(7168), 1309-1312.
MYÎLIBRARY
• Campbell, M. |., Machin, D., & Walters, S. I. (2010).
Medical statistics: A textbook for the health
sciences (4th ed).
• Mateo, M. A., & Kirchhoff, K. T. (Eds.). (2009).
Research for advanced practice nurses:
From evidence to practice.
• Webb, C, & Roe, B. (Eds.). (2007). Reviewing
research evidence for nursing practice:
Systematic reviews.
to zero. Some researchers choose to provide the
CI for the difference of two mean scores instead
of providing a separate CI for each of the mean
scores. In that case, the difference in the mean
scores is said to be statistically significant if its
CI does not include zero (e.g., if the lower limit is
10 and the upper limit is 30). If the CI includes
zero (e.g., if the lower limit is -10 and the upper
limit is 30), we conclude that the observed
difference is not statistically significant.

11. To illustrate this point, let's say that we want
to compare the mean blood pressure (BP) of
exercising and sedentary 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 the non-exercising group.
We notice that the mean BP values of the two
groups differ by 20 mmHg, and we want to
determine whether this difference is statistically
significant. Notice that the range of values
between 120 and 130 mmHg falls within the CIs
for both groups (i.e., the CIs overlap). Thus, we
conclude that the 20 mmHg difference between
the mean BP values is not statistically
significant. Now, say that the mean BP is
120 mmHg (95% CI 110-130 mmHg) 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
of values of the second CI. Thus, we conclude
that the mean BP difference of 20 mmHg is
statistically significant.
Remember, we can use either the CIs of two
mean scores or the CI of their difference to draw
conclusions about whether or not the observed
difference between the scores is statistically
significant. •
10 CANADL!N-NURSE.COM
Copyright of Canadian Nurse is the property of Canadian

12. Nurses Association and its content may not be copied
or emailed to multiple sites or posted to a listserv without the
copyright holder's express written permission.
However, users may print, download, or email articles for
individual use.
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To draw conclusions about a study population,
researchers use samples that they assume truly
represent the population. The confidence
interval (CI) is among the most reliable
indicators of the soundness of their assumption.
A CI is the range of values within which the
population value being studied is believed to fall.
CIs are reported in the results section of
published research and 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

14. from the same population and calculate a range
of estimates for these samples, 95% of the
intervals within the lower and upper limits of
this range will include the population value.
To illustrate the 95% CI of a mean value, say
that a sample of patients with hypertension has
a mean blood pressure of 120 mmHg and that
the 95% CI for this mean was calculated to range
from 110 to 130 mmHg. This might be reported
as: mean 120 mmHg, 95% CI 110-130 mmHg.
It indicates that if other samples from the same
population of patients were generated and
intervals for the mean blood pressure of these
samples were estimated, 95% of the intervals
between the lower limit of 110 mmHg and the
upper limit of 130 mmHg would include the true
mean blood pressure of the population.
Notice that the width of the CI range is a very
important indicator of how reliably the sample
value represents the population in question.
If the CI is narrow, as it is in our example of
110-130 mmHg, then the upper and lower limits
of the CI will be very close to the mean value of
Confidence interval: The range of values, consistent with the
data, that is believed to encompass the actual or
“true” population value
Source: Lang, T.A., & Secic, M. (2006). How to Report
Statistics in Medicine. (2nd ed.). Philadelphia: American
College of Physicians
the sample. This sample mean value is probably a
more reliable estimate of the true mean value of

15. the population than a sample mean value with 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 from the sample
mean of 120 mmHg. In fact, a very wide CI in a
study should be a red flag: it indicates that more
data should have been collected before any
serious conclusions were drawn about the
population. Remember, the narrower the CI, the
more likely it is that the sample value represents
the population value. n
MAHER M. EL-MASRI, RN, PhD, IS AN ASSOCIATE
PROFESSOR AND RESEARCH LEADERSHIP CHAIR
IN THE FACULTY OF NURSINg, UNIVERSITY OF
WINDSOR, IN WINDSOR, ONT.
Confidence intervals: Part 1
TERMInoLogy 101
NurseONE resources
on THIS TopIc
EBSCO-MEDlInE full-text articles
• Hildebrandt, M., Vervölgyi, E., & Bender, R. (2009).
Calculation of NNTs in RCTs with time-to-event outcomes:
A literature review. BMC Medical Research Methodology,
9, 21.
• Hildebrandt, M., Bender, R., Gehrmann, U., & Blettner,
M. (2006). Calculating confidence intervals for impact
numbers. BMC Medical Research Methodology, 6, 32.
• Altman, D. G. (1998). Confidence intervals for the number
needed to treat. BMJ (Clinical Research Ed.), 317(7168),
1309-1312.

16. Myilibrary
• Campbell, M. J., Machin, D., & Walters, S. J. (2010). Medical
statistics: A textbook for the health sciences (4th ed).
• Mateo, M. A., & Kirchhoff, K. T. (Eds.). (2009). Research for
advanced practice nurses: From evidence to practice.
• Webb, C., & Roe, B. (Eds.). (2007). Reviewing research
evidence for nursing practice: Systematic reviews.
8 CANADIAN-NURSE.COM
Copyright of Canadian Nurse is the property of Canadian
Nurses Association and its content may not be copied
or emailed to multiple sites or posted to a listserv without the
copyright holder's express written permission.
However, users may print, download, or email articles for
individual use.