**Statistical Analysis**

In
your proposal you are asked to describe statistical tests for significance that
you will perform on the data that you collect in the evaluation of your
device. Below are two examples of such a
description. Note that each example identifies
the following.

- What data will be collected.
- How many times the
measurement will be repeated.
- The null hypothesis to
be tested.
- The alternative
hypothesis.
- The value of the
probability statistic that is considered significant.

*Example description of
Student’s T Test*

Pressure
drop will be recorded at the given flow rate 5 times for the two stenosis lengths.
The null hypothesis, that pressure drop does not depend on stenosis length will be tested by a one-tailed Student’s T test, under the alternative hypothesis that pressure drop is
larger for longer stenosis. The result will be considered significant for
p values less than 0.05.

*Example description of
Pierson’s Correlation Coefficient*

Pressure
drop will be recorded at 7 flow rates, ranging from 2 ml/sec to 15 ml/sec. A linear least squares fit of these data will
be performed, and the Pierson’s correlation coefficient from this fit will be
evaluated to test the hypothesis that pressure drop depends on flow rate in the
range of flow rates examined. The null
hypothesis is that pressure is not a function of flow rate. Results will be considered significant for p
values less than 0.05.

*Steven A.
Jones*

*Senior Design
(BIEN 400, 402 and 404)*