S Y L L A B U S

 

 

Advanced Biostatistics (BIOL/STAT 336) – Topics in Biostatistics (MATH 488)

Spring Semester, 2006, Mondays and Wednesdays, 4:15 – 5:30pm in Damen Hall, Room 828.

Prerequisites: Some exposure to basic statistical methods or biostatistics (e.g. Stat 203 or 335) including ANOVA

and regression and maturity to move quickly through sophisticated material.

Text: there is no required text for this course; however, students are required to purchase Course Notes, to be

distributed in class.

 

Instructor: Dr. Timothy E. O’Brien                                 Email:  teobrien@gmail.com or tobrie1@luc.edu

Office: Damen Hall, Room 321                                      Office Phone: (773) 508-2129

Office Hours: TBA

Course Web Page: http://www.math.luc.edu/~tobrien/courses/newab/course-homepage.html

 

Course Overview

 

Basic courses in statistics and biostatistics prepare students and researchers to perform simple statistical analyses such as simple linear regression or correlation, paired or two-sample t-tests, one- or two-way ANOVA, and analyses of covariance.  However, practitioners are often faced with other types of data for which these methods are invalid.  These basic statistical analyses have been adapted and generalized to categorical data techniques, generalized and nonlinear regression, multivariate methods and repeated-measures techniques, and survival analysis, and these methods are the focus of this course.  Each of these methods will be motivated with real-life examples.  The focus throughout this course will be on applications, and, as such, theory will not be emphasized. 

 

This course covers the basics of experimental design and analysis, simple and multiple linear regression, generalized linear and nonlinear regression, statistical bioassay and drug synergy, multivariate analysis including MANOVA, repeated measures, and censored data analysis and survival statistics methods (e.g., Cox proportional odds, log-rank tests, Kaplan-Meier estimation).  Students will be required to analyze real-life data sets using the Minitab and SAS statistical packages.  Grading will be based on homework assignments and three exams.

 

Homework and Exams

 

Homework assignments will be given approximately every other week, graded and returned to students in a timely manner.  The first (March 1st) and second (April 19th) exams will be in-class and the final exam will be take-home (and due on or before Saturday, May 6th by 12 noon).

 

Grading Scheme

 

Homework

40%

First Exam

20%

Second Exam

20%

Final Exam

20%

 

Final course (letter) grades will be awarded according to the following grading scheme:

 

[92.5 , 100] = A                         [90.0 , 92.5) = A-

[87.5 , 90.0) = B+                      [82.5 , 87.5) = B                        [80.0 , 82.5) = B-          

[77.5 , 80.0) = C+                      [72.5 , 77.5) = C                        [70.0 , 72.5) = C-

[67.5 , 70.0) = D+                      [60.0 , 67.5) = D                        [0.0 , 60.0) = F

 

Participation

 

Students are expected to attend all classes and to actively participate in classroom discussion.  It is expected that students will read the lecture material before class so as to better benefit from the class lecture and discussion.

 

Computing

 

Students will develop the ability to analyze data sets using the Minitab and SAS software packages, although no previous exposure to these packages will be assumed.  Students are required to have a calculator (needed for homework and exams).

 

 

Academic Honesty

 

It is presumed and required that students do their own work on the homework assignments and all exams.  Discussing homework problems with others is encouraged; however, submitting work as your own which is copied or paraphrased from someone else is not permitted.  This means students may discuss homework problems, but each must write up his/her solutions alone and in one’s own words.  Neither discussing nor copying related to exam questions is permitted.  Cheating includes, but is not limited to, illegal collaboration, copying, using materials not permitted on tests, and assisting others on tests.  Anyone found cheating will not be permitted to withdraw and will receive an “F” grade for the course.  Your academic dean will be informed and a statement will be placed in your permanent file.

 

 

Preliminary Semester Schedule

 

Monday

Wednesday

 

18 Jan – Review of t-tests, regression, and ANOVA (1)

23 Jan – Linear regression (2)

25 Jan – Linear regression (2)

30 Jan – Linear regression (2)

 1 Feb – Experimental Design (3)

 6 Feb – Experimental Design (3)

 8 Feb – Experimental Design (3)

13 Feb – Experimental Design (3)

15 Feb – GdLM’s (4)

20 Feb – GdLM’s (4)

22 Feb – GdLM’s (4)

27 Feb – GdLM’s (4)

 1 Mar – First exam

 6 Mar – Spring Break

 8 Mar – Spring Break

13 Mar – Nonlinear models (5)

15 Mar – Nonlinear models (5)

20 Mar – Nonlinear models (5)

22 Mar – Bioassay and Synergy (6)

27 Mar – Bioassay and Synergy (6)

29 Mar – Bioassay and Synergy (6)

 3 Apr – Bioassay and Synergy (6)

 5 Apr – Mixed models and RMDs (7)

10 Apr – Mixed models and RMDs (7)

12 Apr – Mixed models and RMDs (7)

17 Apr – Survival Analysis (8)

19 Apr – Second exam

24 Apr – Survival Analysis (8)

26 Apr – Multivariate Methods (9)

 1 May – Multivariate Methods (9)

 3 May – Multivariate Methods (9)

 

Note #1:  The first exam will take place on March 1st and second exam will take place on April 19th, and will be open book-open notes and 75-minutes in length.  The final exam will be take home, given out at the end of class on the last class and will be due on or before Saturday, May 6th by 12 noon.

 

Note #2:  The last day that a student may withdraw without a penalty grade of “WF” is Monday, March 27th at 5:00pm.