BME 3710 Biomedical Engineering Data Evaluation Principles
INSTRUCTORS: Hamid Shahrestani
OFFICE: EC 2677
OFFICE HOURS: MWF
An Introduction to Medical Statistics, Third Edition
Recommended (Very Highly)
Introduction to Statistical Quality Control, Fourth Edition
Douglas C. Montgomery
John Wiley & Sons, Inc.
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:
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%
Session Topic Reference
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
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
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