BME 3710 Biomedical Engineering Data Evaluation Principles
Fall 2005
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INSTRUCTORS: Hamid Shahrestani
OFFICE: EC
2677
OFFICE HOURS: MWF
PHONE:
954-937-6479
EMAIL: shahresh@fiu.edu
Textbook: Required
An
Introduction to Medical Statistics, Third Edition
Martin Bland
Recommended
(Very Highly)
Introduction
to Statistical Quality Control, Fourth Edition
Douglas C.
Montgomery
John Wiley & Sons, Inc.
Class Description:
This is a second course in statistics for
students in the BS program in biomedical engineering. The course covers application of statistical
and data evaluation methods to the practice of biomedical engineering. The course topics can be divided into the
following three areas:
Course Outcomes:
By the end of
this course, students should be able to:
1. Use the SPSS software package to compute
basic statistical measures and present data in a variety of graphical outputs.
2. Compute probabilities of events and
interpret probability density functions.
3. Determine confidence intervals for data
and perform statistical hypothesis testing.
4. Compute and interpret linear correlations
between data.
5. Develop and interpret control charts for
statistical process control.
6. Design experiments to optimize a process,
and interpret the resulting data.
7. Appropriately design clinical
experimental and observational studies.
8. Estimate the repeatability, sensitivity,
and specificity of clinical measurements.
9. Determine the appropriate sample size and
resulting statistical power for a given study design.
10. Choose the appropriate statistical method
for a given problem and data set.
POINTS DISTRIBUTION: Assignments 10%
Exam
I 20%
Exam
II 20%
Project
and Presentation 15%
Final
Exam 35%
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Session Topic Reference
Note:
Chapter #’s in italics are from
Basic
Probability and Statistics for Medical Sciences
1
Introduction
and scope of the class Chapter
1
2
Summarizing
and presenting data Chapters
4,5
3
Probability
– Binomial and normal distributions Chapters
6,7
4
Estimation
– confidence intervals Chapter
8
5
Significance
tests Chapter
9
6
Comparing
means of small samples – the t-test Chapter
10
7
Comparing
means of small samples – ANOVA Chapter
10
8
Regression
and Correlation Chapter
11
9
Review
Statistical Process Control and Design of
Experiments for Process Optimization
11
Guest
Lecture
12
Introduction
to Statistical Process Control Chapter
4
13
Control
Charts for variables Chapter
5
14
Control
Charts for attributes Chapter
6
15
Factorial
experiments for process design and improvement Chapter
12
16
Process
optimization with designed experiments Chapter
13
17
Review
Application
of Statistical and Probabilistic Methods to Clinical Data
19
Guest
Lecture
20
Design
of clinical experimental studies Chapter
2
21
Design
of clinical observational studies Chapter
3
22
Clinical
measurement – repeatability, sensitivity, specificity Chapter 15
23
Determination
of sample size Chapter
18
24
Choosing
the statistical method Chapter
14
25
Project
Presentation
FINAL
EXAM
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