# This is a test by dfhdhdhdhjr

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```									Review of Statistics for
Pulmonary Lab

C. S. Tritt, Ph.D.
April 11, 2006
Why Bother with Statistics?
 There   is always some uncertainty
in measured values.
 It is often impractical to sample
an entire population, so some
subset must be selected and
measured and the result used to
draw a conclusion about the
population.
2
Why Bother with Statistics?
 Statistics quantifies the inherent
uncertainties of experimental
research.
 Statistics allows uncertainty to be
quantified. This can prevent
disputes in the interpretation of
results.

3
Hypothesis
 Nearly all experimental
investigations should start with
one or more hypothesis.
 Statistical methods are often used
to test these hypothesis.
 This lab provides a specific
example of this type of use of
statistics.
4
Test Statistics
 In hypothesis testing, a test statistic
is typically calculated from the
observed data.
 This value is then compared to an
expected value based on a
mathematical analysis of the general
situation.
 If the test statistic is greater than
the expected value, reject the
hypothesis than your sample
matches the expected situation.
5
Comparison of Means
 In this lab, you were asked to
compare your results with accepted
values of certain pulmonary
volumes.
 These volumes and there values
are:
 TV = 500 ml
 IRV = 1900 ml
 ERV = 700 ml

   In general, t-test’s are used for the
comparison of means.
6
TV, IRV & ERV Instructions
 Excel has some a built in data analysis
tools. These are listed under the Tools
| Data analysis menu choice.
 However, it do not appear to be able
to make comparisons between
samples and known values so some
manual calculations were required.
 Alternatively, you may be able to use
Minitab or some other statistical
analyses software to do your analysis.
7
VC Instructions
 In this experiment you will be
comparing observed and predicted
VC values.
 I suggest you use unpaired t-tests
(although paired tests might be
better) not assuming equal
variances to do this.
 In this case, since you have a
different predicted value for each
subject, the variance of the
predicted values can be calculated.
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My Results (part 1)
 See NursesPulmVolResultWork.xls.
 Note use of sheet labels.
 Note layout of table with calculated
(function) values.
 Note entry of expected values for
TV, IRV and ERV.
 Note use of prediction equation.

9
My Results (part 2)
 Note location and labeling of
statistical test results.
 Note identity plot for VC.
 Note formatting of numeric values
(significant digits).
 Note formatting of gridlines, axis
labels and initials.
 Did not do RV calculations.
 Did not use paired t-tests.

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