University of Pittsburgh

BIOST 2042 Sample Syllabus

University of Pittsburgh Graduate School of Public Health

Department of Biostatistics

BIOST 2042- Introduction to Statistical Methods II

3 Credit Hours

Spring Term, 2009




John W. Wilson, Ph.D.

            Department of Biostatistics and NSABP Biostatistical Center

            350 Sterling (201 N. Craig St., Suite 350), 412 / 383-1648

            A-437 Crabtree, 412 / 624 - 3011

Office Hours:  Monday and Wednesday, 9 – 10:30am





Teaching Assistant:

            Nathan Pugh

            A-432 Crabtree Hall , 412 / 624 - 3063

            Office Hours:  Tuesdays 3 – 4:30 pm and Thursdays 9:30 – 11am



Class Meetings:

Monday and Wednesday, 11:00 – 12:15

G-23 Parran Hall


First meeting:  5 January 2009

Last meeting:   22 April 2009 (Final Exam)



Course Summary:


BIOST 2042 continues the introduction to applied biostatistical methods begun in BIOST 2041 (Introduction to Statistical Methods I).  The course presents aspects of univariate regression, 1- and 2-way analysis of variance, analysis of covariance, categorical analysis, and survival analysis. 




BIOST 2041 or equivalent introduction to statistical methods.

Teaching / Learning Objectives:


Upon completion of this course, students should


1) understand basic regression analysis, analysis of variance, analysis of covariance, and survival analysis.


2) further their understanding of categorical data analysis.


3) use statistical software to analyze data sets illustrating the above statistical methods.


4) recognize when these methods are and are not applicable.




Fundamentals of Biostatistics by Bernard Rosner, 6th edition. 

Make sure you obtain a copy with a CD!



Supplemental Material:


The CD that comes with the text has supplemental problems with worked-out answers.  As the course proceeds, I will list appropriate supplemental problems on the course website and I encourage you to look through these problems.  They offer additional practice if you’re feeling uncertain of your understanding of a given topic and the problem answer details can help you see how to solve future problems of the same type.



Statistical Software:


The homework assignments will require a statistical package for computations.  The “official” package supported in this course is SAS, which is available on the machines at the computer labs on campus.  Pitt students, staff, and faculty can obtain a 1-year copy of SAS from the software licensing service in Bellefield Hall.


It is not strictly necessary to use SAS for the homework assignments.  Stata, S-Plus, R, NCSS, SPSS, Systat, and other packages will also perform the required procedures.  Be aware, however, that the course instructor is most familiar with Stata and SAS and can be relied on to answer questions about those packages only.  So, for instance, if you use SPSS, you will have to find another source of information about that package’s syntax, etc.


Excel and Instat are not recommended because they do not include all the procedures that will be required in BIOS 2042 and many research settings.



Course Requirements and Grading:


There will be midterm and final exams and approximately 8 homework assignments.   The contribution of each of these assessments toward the final grade will be as follows:


1/3       Homework

1/3       Midterm Exam

1/3       Final Exam


One homework assignment will be dropped from your homework grade.  In other words, if there are 8 assignments, the best 7 will contribute toward your homework grade.  This will make it possible not to be penalized if you cannot turn in an assignment when it is due (because of professional meeting, illness, etc.).


We strongly prefer to receive the homework on paper.  However, if you are unable to attend class when an assignment is due, you may send the assignment via e-mail.


Exams and homework will cover material presented in class only.  Rosner’s text presents far more material than could ever be covered in a one-semester class.  Although you should read the sections of Rosner that pertain to a given unit/class (see reading assignments in the tentative class schedule), you are not responsible for Rosner material that was not discussed in lecture.


All “for credit” grades will be letter grades only (A, B, C, D, F).

Course web site:       


This course will make use of Blackboard, which is accessible on (Log in and click the link to BIOST 2042.).  Lecture notes, homework assignments, supplemental materials, and other information will be posted on this website. 


Blackboard requires a “” username to log in and any course-related mail will be sent to this address only.  If you wish your course e-mail to be forwarded to another account, open and set your forwarding address.  Otherwise, you will not be alerted to course news, such as corrections of typos in lecture notes or homework, last-minute class cancellation, etc.


Some Concrete Suggestions for Success in the Course:


  1. Obviously, you should review the lecture notes and attend class.  Although the notes will be posted on the course website prior to class, there are often blank areas that I fill in at the overhead projector.  In addition, I will often amplify explanations or present new material using blank overheads at the projector.  Therefore, do not assume that having the posted notes tells you all the material for which you are responsible on homework assignments and exams.


  1. Homework assignments will often consist of 2 parts, one part that I ask you to turn in and another part you do not turn in.  Resist the temptation to skip the problems that won’t be turned in.  Often, they are the only practice I will assign for certain concepts or procedures, which you will be responsible for on an exam.


  1. Ask questions!!!!  Many students feel shy about asking questions during or after class. It is easy to feel that a question is “stupid” and not worth asking.  There is no such thing as a stupid question!  If you have a question, someone else in the class is probably wondering the same thing.  You will help other students as well as yourself if you speak up.

Accommodation for Students with Disabilities:

If you have a disability for which you may require accommodation, you are encouraged to contact both your instructor and Disability Resources and Services, 216 William Pitt Union (412.648.7890 or TTY 412.383.7355), as early as possible in the term. DRS will verify your disability and determine reasonable accommodations for this course. A comprehensive description of the services of that office can be obtained at

Academic Integrity:


All students are expected to adhere to the standards of academic honesty.  Any work submitted by a student must represent his/her own intellectual contribution and efforts.  Any student found to be engaged in cheating, plagiarism, or any other acts of academic dishonesty will be subject to a failing grade in the assignment and/or the course and to further disciplinary action.


Other course policies:


  1. All work submitted on homework and exams must be your own.  For homework, you may discuss problem solutions with other students.  When you write up the assignment, however, do any necessary computer work and write the answers yourself.  This policy exists for 2 reasons.  First, obviously, we want your grade to represent your own work.  Second, it is important to know how to write up the major features of an analysis. Doing so for homework is a good way to get more comfortable with this process.


  1. Please set pagers & cell phones to a silent mode during class.


  1. If you are late to class, please sit in the back of the lecture hall.


  1. Homework will be due in class on the designated day without exception! The reason is that homework keys will be posted and assignments will be discussed in class on the day they're due. For obvious reasons, it will not be possible to allow late homework.  If you are unable to submit an assignment, send me an explanation via e-mail so that I can keep track of “excused” assignments!!

Tentative Schedule of Sessions, Reading Assignments, and Homework Assignments:


Dates (2009)

Topics and Reading Assignments

Homework Assignments


5 January



Unit 1a.  Introduction to regression & general concepts (§ 11.1)




5 & 7 January



Unit 1b.  Definition and point estimation of regression parameters (§ 11.2 – 11.3)



HW 1 assigned (7 Jan.)


7 & 12 January



Unit 1c.  Interval estimation for intercept and slope and hypothesis testing for 0 slope. 




12 January



Unit 1d.  Analysis of Variance Table and R2.



14 January



Unit 1e.  Confidence and prediction intervals (§ 11.4 – 11.5).


HW 1 due,

HW 2 assigned (14 Feb.)


14 & 21 January



Unit 1f.  Assessing regression assumptions  (§ 11.6)



HW 2 due


21 January



Unit 1g.  Outliers and influence. (§ 11.6)




26 January



Unit 1h.  Nonparametric regression.


HW 3 assigned


26 & 28 January



Unit 1i. Indicator variables in regression 



Tentative Schedule (continued)

Dates (2009)

Topics and Reading Assignments

Homework Assignments


2 & 4 February



Unit 2.  Introduction to correlation. (§ 11.7 - 11.8, 11.12)

HW 3 due,

HW 4 assigned (2 Feb.)


9 February





HW 4 due


11 February



Midterm Exam




16 February



Unit 3a.  One-way analysis of variance (§ 12.1 – 12.3).




18 & 23 February



Unit 3b.  Exploration of group differences.  Linear contrasts.



HW 5 assigned (18 Feb.)


25 February & 2 March



Unit 3c. Multiple comparisons (§ 12.4).


HW 5 due (25 Feb.)


4 March



Unit 3d.  Randomized Blocks


HW 6 assigned


16 & 18 March



Unit 3e.  Two-way analysis of variance (§ 12.6).


HW 6 due (18 March)


18 & 23 March



Unit 3f.  Fixed, random, and mixed effects models.



25 March



Unit 3g.  Assessment of ANOVA assumptions.


HW 7 assigned


Tentative Schedule (continued)

Dates (2009)

Topics and Reading Assignments

Homework Assignments


25 March



Unit 3h.  ANOVA as regression with indicator variables.



30 March



Unit 3i.  Nonparametric ANOVA  (§12.7)



1 – 6  April



Unit 4a.  Stratified categorical data (§ 13.3 – 13.5)


HW 7 due (1 April)


8 April



Unit 4b.  Ordered categorical data


HW 8 assigned


13 April



Unit 5a.  Introduction to survival and censored data (§ 14.8).




15 April



Unit 5b.  Kaplan-Meier survival curves and log-rank tests (§ 14.9 – 14.10).


HW 8 due


20 April






22 April



Final Exam



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