- e-mail address: sungkyu (at) pitt.edu
- Office: CL 2734
- Phone: 412-624-9033
- Office Hours: Thursdays 11:15-12:15, or by appointment

- e-mail address: qiw31 (at) pitt.edu
- TA’s office hours: Mondays 3:00 - 5:00 at Reading Room (CL 2712)

- Final Exam: Take-home. Thursday, Dec. 4 (7PM) to Friday, Dec. 5 (Midnight).
- Problems (Part I: SAS, Part II: R) : Download the exam here
- Datasets: hypertension.dat is contained in the SAS dataset. college.txt
- Solution code for final exam
- Complete and submit through the Courseweb.
- Check your previous homework and midterm grades.
- Complete OMET survey.
- Datasets and programs + Handouts for R lectures
- Homeworks
- Midterm II: Thursday, November 20. Open book. Open notes. No electronic devices.
- Instructor's office hour on that day is shifted to 2-3PM.
- Practice Exam 2 (from Dr. Sovak) and solutions
- Also see the rest of problems below.
- Midterm I: Tuesday, September 30. Open book. Open notes. No electronic devices (no SAS!).
- Answer key to Midterm I
- Practice Exam (from Dr. Block) with solution : To prepare midterm I on September 30, look at problems 1 and 2(a)-(c).
- Practice Exam (from Dr. Sovak) : To prepare midterm I on September 30, look at problems 1 and 2.
- No class on Thursday, October 2.

- use Statistical software (SAS and R) to handle data,
- choose correct methods of data analysis,
- perform data analysis;
- interpret results correctly and effectively.

- SAS is available on the PCs at all campus computing labs, such as Cathedral, Posvar, Forbes Quad and Benedum. If in addition you would like to have SAS on your PC, Pitt's Software Download Service offers SAS for free. SAS can only be installed on Windows or Unix environments (No Mac OS).
- R
is a free, open-source software package/programming language for
statistical computing, and is available on the PCs at all
campus
computing labs, such as Cathedral, Posvar, Forbes Quad and
Benedum. If in addition you would like to have R on your
PC/Mac/Unix, it can be downloaded for free at http://www.r-project.org/

- Peter Dalgaard, Introductory Statistics with R, Second Edition, Springer, New York, NY (ISBN: 978-0387790534)
- Geoff Der and Brian S. Everitt, A Handbook of Statistical Analyses using SAS, Third Edition, Chapman and Hall/CRC, London, UK, (ISBN: 978-1584887843)

- Handbook of Biological Statistics by John H. McDonald http://www.biostathandbook.com/

- The little SAS book: a primer, fifth edition by Delwiche, Lora D; Slaughter, Susan J 2012 ( eBook available at Pitt library)
- support.sas.com
- UCLA idre SAS help page
- SAS/STAT User Guide for Versions 7 and 8 (OUTDATED) provides links to pdf documents on popular procedures.

- A Beginner's Guide to R by Alain F. Zuur, Elena N. Ieno, Erik Meesters 2009 (Springer), eBook available at link.springer.com
- The official intro, "An Introduction to R", available online in HTML and PDF
- John Verzani, "simpleR", in PDF
- Google R Style Guide offers some rules for naming, spacing, etc., which are generally good ideas
- Quick-R. This is primarily aimed at those who already know a commercial statistics package like SAS, SPSS or Stata, but it's very clear and well-organized, and others may find it useful as well.
- Patrick Burns, The R Inferno. "If you are using R and you think you're in hell, this is a map for you."
- Thomas Lumley, "R Fundamentals and Programming Techniques" (large PDF)
- Paul Torfs & Claudia Brauer, "A very short intro to R"
- UCLA idre R help page
- Avril Coghlan, a Little Book of R for Multivariate Analysis

RStudio is an "integrated development environment" (IDE) for R. Using it is not required, but strongly recommended, because it gives everyone, on all computers, a common working environment.

- Many links and material will be made progressively available at the current page.
- Assignments are submitted and graded electronically through CourseWeb/Blackboard.

- Midterm I, 20% - Tuesday, September 30
- Midterm II, 20% - Thursday, November 20
- Homeworks 30%
- Final 30% - Saturday, December 13, 10:00 AM - 12:00 AM

SAS - SAS Basics - SAS ch1

SAS - Inference for numerical data- ch2

SAS - Inference for categorical data - ch3

SAS - Analysis of Variance - ch4-ch5

SAS - Linear Regression - ch6-ch7

SAS - Analysis of Variance of Repeated measures - ch11

SAS - Advanced topics - little SAS book ch 4-5 (4.13-4.16, 5.1-5.3).

R - Basics - R ch1-2

R - Probability and Distributions - R ch3-

R graphics - R ch4

R - t-tests - R ch5

R - Analysis of Variance - ch7

R- Inference for categorical data - ch8

R - Power calculation - ch9

Students in this course will be expected to comply with the University of Pittsburgh's Policy on Academic Integrity. Any student suspected of violating this obligation for any reason during the semester will be required to participate in the procedural process, initiated at the instructor level, as outlined in the University Guidelines on Academic Integrity. This may include, but is not limited to, the confiscation of the examination of any individual suspected of violating University Policy. Furthermore, no student may bring any unauthorized materials to an exam, including dictionaries and programmable calculators.

Disability Services

If you have a disability for which you are or may be requesting an accommodation, you are encouraged to contact both your instructor and Disability Resources and Services (DRS), 140 William Pitt Union, (412) 648-7890, drsrecep@pitt.edu, (412) 228-5347 for P3 ASL users, as early as possible in the term. DRS will verify your disability and determine reasonable accommodations for this course.

Copyright Notice

Course materials may be protected by copyright. United States copyright law, 17 USC section 101, et seq., in addition to University policy and procedures, prohibit unauthorized duplication or retransmission of course materials. See Library of Congress Copyright Office and the University Copyright Policy.