Lab 7 Template 1. Using the data you collected for the Week 5 Lab (heights of 10 different people that you work with plus the 10 heights provided by your instructor), discuss your method of collection for the values that you are using in your study (systematic, convenience, cluster, stratified, simple random). What are some faults with this type of data collection? What other types of data collection could you have used, and how might this have affected your study? Use the Week 6 Spreadsheet to help you with calculations for the following questions/statements. 2. Give a point estimate (mean) for the average height of all people at the place where you work. Start by putting the 20 heights you are working with into the blue Data column of the spreadsheet. What is your point estimate, and what does this mean? 3. Find a 95% confidence interval for the true mean height of all the people at your place of work. What is the interval? 4. Give a practical interpretation of the interval and explain carefully what the output means. (For example, you might say, "I am 95% confident that the true mean height of all of the people in my company is between 64 inches and 68 inches"). 5. Post a screenshot of your work from the t value Confidence Interval for µ from the Confidence Interval tab on the Week 6 Excel spreadsheet. 6. Now, change your confidence level to 99% for the same data, and post a screenshot of this table/interval, as well. 7. Compare the margins of error from the two screenshots. Would the margin of error be larger or smaller for the 99% CI? Explain your reasoning. 8. Save this template with your answers and include your name in the title. 9. Submit the document. J LU 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 outcomes: A literature review. BMC Medical Research Methodology, 9,21. • Hildebrandt, M., Bender, .

1. Lab 7 Template
1. Using the data you collected for the Week 5 Lab (heights of
10 different people that you work with plus the 10 heights
provided by your instructor), discuss your method of collection
for the values that you are using in your study (systematic,
convenience, cluster, stratified, simple random). What are some
faults with this type of data collection? What other types of data
collection could you have used, and how might this have
affected your study?
Use the Week 6 Spreadsheet to help you with calculations for
the following questions/statements.
2. Give a point estimate (mean) for the average height of all
people at the place where you work. Start by putting the 20
heights you are working with into the blue Data column of the
spreadsheet. What is your point estimate, and what does this
mean?
3. Find a 95% confidence interval for the true mean height of all
the people at your place of work. What is the interval?
4. Give a practical interpretation of the interval and explain
carefully what the output means. (For example, you might say,
"I am 95% confident that the true mean height of all of
the people in my company is between 64 inches and 68 inches").

2. 5. Post a screenshot of your work from the t value Confidence
Interval for µ from the Confidence Interval tab on the Week 6
Excel spreadsheet.
6. Now, change your confidence level to 99% for the same data,
and post a screenshot of this table/interval, as well.
7. Compare the margins of error from the two screenshots.
Would the margin of error be larger or smaller for the 99% CI?
Explain your reasoning.
8. Save this template with your answers and include your name
in the title.
9. Submit the document.
J
LU
TERMINOLOGY 101

3. 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
outcomes: A literature review. BMC Medical

4. 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.

5. 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
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6. 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
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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
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

8. 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
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

9. 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.
Myilibrary
• Campbell, M. J., Machin, D., & Walters, S. J. (2010). Medical
statistics: A textbook for the health sciences (4th ed).

10. • 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.