Abbreviated Course Title (19 spaces or less):

BME Data Eva Prin

 

Catalog Description (200 spaces or less):

Design and analysis of clinical and biomedical experiments. Statistical process control and measuring performance relevant to medical device industry.

 

 

Course Objectives:

This is the second course in statistics for students in the BS program in biomedical engineering.  The course covers various statistical and data evaluation methods and their usages in biomedical engineering.  It provides education in the quantitative analysis and evaluation of medical and biological data, and hence adequately prepares graduates for advanced studies in engineering or medicine and for professional practice as biomedical engineers in industry or as researchers.

 

Major Topics:

1.      Basic Probability and Statistics for Medical Sciences

2.      Control and Design of Experiments for Process Optimization

3.      Application of Statistical and Probabilistic Methods to Clinical Data

 

Co-requisites:

NA

 

Prerequisites:

STA 3033-Intro Probability & Statistics

 

Contact Hours per Week: Lecture: ___3__ ,  Lab: __0___ ,  Field Work: ___0__

 

Textbook(s):

1.      An Introduction to Medical Statistics, Third Edition, Oxford Medical Publications

by Martin Bland (Required)

 

2.      Introduction to Statistical Quality Control, Fourth Edition, John Wiley & Sons, Inc.

by Douglas C. Montgomery (Recommended)

 

Course Learning Outcomes:

 

No.

Course Learning Outcome

Corresponding BSBME Program Learning Outcome (LO) and Metric (M)

1

Apply statistical methods to the design of experiments and analysis of biological and medical data.

LO-1, 2, 8

2

Apply statistical methods to multi-disciplinary problems and projects involving biomedical engineering.

LO-1,2

3

Calculate probabilities of events and interpret probability density functions.

LO-1

4

Determine confidence intervals for data and perform statistical hypothesis testing

LO-1

5

Calculate and interpret linear correlations between data

LO-1

6

Develop and interpret control charts for statistical process control.

LO-1

7

Design experiments to optimize a process and interpret the resulting data.

LO-2

8

Estimate the repeatability, sensitivity and specificity of clinical measurements.

LO-1

9

Use the SPSS software package to compute statistical measures and present data in a variety of graphical outputs.

LO-1,5

 

Metric Definition:

1-1: Exam 1 in-class

2-1: Exam 2 in-class

F: Final exam

P: Project

 

 

BSBME Program Learning Outcomes

 

  1. Ability to apply knowledge of mathematics (including differential equations and statistics), physical and life sciences, and engineering to carry out analysis and design to solve problems at the interface of engineering and biology;
  2. Ability to design and conduct experiments, as well as to measure, analyze and interpret data from living systems;
  3. Ability to design a system, component, or process to meet desired needs, including systems that involve the interaction between living and non-living materials;
  4. Ability to identify, formulate, and adapt engineering solutions to unmet biological needs,
  5. Ability to use the techniques, skills, and modern engineering tools necessary for engineering practice, including the ability to model and analyze biological systems as engineering systems;
  6. Ability to function on multi-disciplinary teams;
  7. Ability to communicate effectively;
  8. Awareness of the characteristics of responsible professional engineering practice, including ethical conduct, consideration of the impact of engineering solutions on society in a global and contemporary context, and the value of life-long learning.  

POINTS DISTRIBUTION:               

Assignments        10%

Exam I     20%

Exam II   20%       

Project and Presentation     15%

Final Exam             35%

 

 

TENTATIVE COURSE OUTLINE

Session  Topic      Reference

                                                Note: Chapter #’s in italics are from Montgomery

 

Basic Probability and Statistics for Medical Sciences

Introduction and scope of the class                                                 Chapter 1

Summarizing and presenting data                                                     Chapters 4,5

Probability – Binomial and normal distributions                             Chapters 6,7

Estimation – confidence intervals                                                     Chapter 8

Significance tests                                                                                 Chapter 9

Comparing means of small samples – the t-test                              Chapter 10

Comparing means of small samples – ANOVA                               Chapter 10

Regression and Correlation                                                                Chapter 11

Review

EXAM I

 

 

Statistical Process Control and Design of Experiments for Process Optimization

Guest Lecture

Introduction to Statistical Process Control                                     Chapter 4

Control Charts for variables                                                               Chapter 5

Control Charts for attributes                                                              Chapter 6

Factorial experiments for process design and improvement         Chapter 12

Process optimization with designed experiments                           Chapter 13

Review

EXAM II

 

 

Application of Statistical and Probabilistic Methods to Clinical Data

Guest Lecture (Dr. Dan Tobarti)

Design of clinical experimental studies                                            Chapter 2

Design of clinical observational studies                                          Chapter 3

Clinical measurement – repeatability, sensitivity, specificity       Chapter 15

Determination of sample size                                                             Chapter 18

Choosing the statistical method                                                        Chapter 14

Project Presentation

FINAL EXAM