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Applied Statistics

Statistical Computing - 511

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Applied Statistics

25 University Ave
West Chester, PA 19383

Phone: 610-436-2440
Email: Randy Reiger

Introduction to Statistical Computing - 511

Completion of the course will give a student the ability to use a computer to effectively manage and manipulate data, conduct basic statistical analyses, and generate reports and graphics. This course will also introduce the student to the basic tenets of computer programming language and syntax.

Topics: This class will begin with a very general introduction to statistical programming using the SAS System. We will learn the important features of various types of data sets  and files. We will talk about data entry and data management techniques. Through hands-on examples, we will learn how to import and export data, merge related data sets, conduct simple statistical procedures on data sets, and generate appropriate charts, plots, reports, and graphics. We will emphasize basic programming skills necessary for
effective statistical programming, such as if-then loops, random number generation, treating missing data, and transforming variables

Tentative Schedule of Weekly Topics

  1. Overview of Data Management, Definitions of Basic Terms, Introduction to Computers and Operating Systems, Features of Various Types of Data Files
  2. Introduction to SAS, Structure of SAS, SAS data sets, SAS statement syntax, SAS Output, Running a SAS program.
  3. Using SAS Procedures: Printing Data Sets, Charts and Plots
  4. Frequency Tables and Cross-tabulations, Descriptive Statistics
  5. Sorting Data, Subgroup Processing
  6. Creating Data Sets, Creating and Transforming Variables
  7. Statistical programming: Declarative Statements, Conditional Execution, Missing Values
  8. Statistical programming (continued), Reading/Importing Data Sets
  9. Multiple Input Data Sets, Special Variables, Multiple Output Data Sets
  10. Report Writing Procedures (PROC TABULATE)
  11. Introduction to SAS/IML
  12. Statistical Graphics using SAS/Graph
  13. Introduction to Selected SAS Statistical Procedures (GLM, REG)
  14. Writing MACROS
  15. Managing SAS Libraries

Read the Course Descriptions

Example Syllabus

STA511: Intro to Statistical Computing

Instructor: Dr. Randall H. Rieger

Office: Room 116 in 25 University Ave. Building

Email Address:

Office Telephone: (610) 436-2893

Office Hours: Monday 3:30-5:30, Tuesday 3:30-5:30, Wednesday 3:00-4:00

Class Time: Mon 5:45 - 8:30

Classroom: 25 University Ave – Room 158 (and 103) (I think)

Campus Emergencies
For campus emergencies call WCU’s Department of Public Safety at (610)436-3311

Required Text:
Delwiche and Slaughter, The Little SAS Book, 3rd edition, SAS Publishing, Cary, NC 2004

Supplemental Texts:
Elliott, Learning SAS in the Computer Lab, Duxbury Press, 1999
Cody and Smith, Applied Statistics and SAS Programming Language, 4th ed., Pearson Education, 1997
Many others

Statistics Texts

In order to review very basic statistical topics used in this class, you may want to have an introductory (non-mathematical) statistics textbook to use for reference, such as:
Brase and Brase, Understanding Basic Statistics, 3rd ed., Houghton Mifflin, New York, 2007.
Alternatively, any introductory mathematical statistics text book will serve this purpose on a more theoretical level. The following are recommended: Hogg and Tanis, Probability and Statistical Inference, Prentice Hall or Wackerly, Mendenhall and Sheaffer, Mathematical Statistics with Applications, Duxbury

SAS Software

The SAS Statistical software package is available free to any West Chester University student. The software can be loaded from a DVD onto a student's PC. The method of distributing the DVD’s to interested students will be discussed on the first day of class. As part of the licensing agreement, upon graduating from or leaving WCU, the software will expire and no longer be available for the student's use. In addition, the SAS software (and other statistical packages) will be available on all computers in the Applied Statistics Laboratory.

Graduate Assitants As an additional resource, four graduate assistants in the Applied Statistics MS Program will be available at various times to assist students with questions, assignments, and for additional practice. Please bear in mind that most of these students are also taking this class, so they should only be expected to provide collaborative discussion, not tutoring or teaching. Their hours and location will be provided on the first day of classes.

Day Time Location GA
Sunday 7-10pm UNA Room 103 Rotating
Monday 3:15-5:15pm Mitchell 408 Grace Li
Tuesday 3:15-5:15pm Mitchell 408 Matthew Baldwin
Wednesday 3:15-5:15pm Mitchell 408 Flora Zhou
Thursday 3:15-5:15pm Mitchell 408 Jennifer Krantz
Course Objectives:

By the end of the course, students should be able to manage, manipulate, and perform basic statistical procedures on actual data sets using SAS. Students will learn the basic tenets of statistical computer programming, as well as the skills necessary to produce and interpret descriptive reports and graphics. Students will also have the background and training to complete the Base SAS Programming Certification Exam.

Topics:We will cover the SAS Windowing environment, data libraries, data entry, the DATA step, basic programming techniques, working with data sets, SAS statistical procedures, report writing, graphics, and interpretation of output.

Assignment % of Grade
Exam 1 - (written, in class) 16%
Exam 2 (computer, take home) 21%
Exam 3 (written, in-class) 20%
Final Exam (computer, take home) 22%
Homework 16%
Participation  5%
Class Format:
  • Most classes will consist of
    1. a 60-90 minute lecture/presentation introducing new material
    2. a "LAB" assignment to be completed in class
    3. a distributed homework assignment to be worked on independently outside of class.
  • All homework assignments, lecture notes, and LAB assignments will be made available prior to class on the class blackboard web page. It is the student's responsibility to print the appropriate materials and bring them to class. Please do not wait until class to print the materials.
  • Homework assignments will be collected and graded.
  • While you are strongly encouraged to discuss aspects of problems and assignments with classmates, the write-up of all assignments and the actual programming MUST be done independentlyunder the guidelines of the Honor Code. If you have questions, Dr.Rieger or the Graduate Assistants will be glad to help you.
  • On take-home examination assignments, students must work independently under the guidelines of the Honor Code.If you have questions, Dr. Rieger will be glad to help you.
  • EXAM I will be a 60 minute, written, in-class examination. EXAM II will be a one-week computer-based, take-home examination. EXAM III will be a 60 minute, written, in-class examination
  • The Final Exam will be a computer-based, take-home exam.
  • Missed exams can only be made up with a valid, verifiable, written university-approved excuse and must be made up within a week of the originally-scheduled exam.
  • Late or missing homework assignments will only be excused by a valid, verifiable, written university-approved excuse.
Class Rules
  • Students engaging in disruptive behavior will be dealt with according to university policy. Students are encouraged to consult the undergraduate catalog for details of this policy
  • If there is an emergency or unsafe situation while you are in class or on campus, please call 610-436-3311 immediately.
  • Academic dishonesty will not be tolerated in this class. Any cases of academic dishonesty will be dealt with according to university policy, and I will recommend the maximum possible penalty.
  • Students with disabilities are encouraged to make their needs known to the instructor and the Office of Services for Students with Disabilities early in the semester.
  • Please make use of office hours and other department and university resources if extra help is needed.
  • In the event that I am unable to meet a class, I will a) notify you in person at a prior time or b) an official class cancellation notification on the stationary of the Department of Mathematics, signed and date stamped by the Department Secretary (BarbaraMaleno) will be posted on the classroom door. All other postings announcing the cancellation of this class are to be considered unofficial and are to be ignored.
  • Students should bring a storage device to each class to save any relevant lab work.
Class Philosophy
  • This should be a fun class where you will learn valuable skills. By the end of this class, you will be proficient in working with data. In subsequent classes, we will learn more advanced statistical techniques, and you will be able to pick up the computer part of these techniques easily. However, in order to truly learn the skills of computer programming, you must give yourselves time to "play around" with assignments. If you wait until the night before class to do your work, it will be hard to be successful in this class.
  • Students are encouraged to give me feedback about the class. If you have any suggestions about any aspect of the class, please let me know in person or via e-mail or a note in my box. I will do whatever I can to optimize your learning experience in this class. However, I need to know what you are thinking!
  • “The fastest way to achieve success is to increase your rate of failure.” Sometimes more can be learned by struggling through a problem and allowing yourselves several iterations at solving it. Please have the confidence and resolve to not give up on a problem or idea until giving it maximum effort. I guarantee that all of you will have moments of great frustration while trying to solve a problem. But, learning to persevere and think critically under stress is one of the skills I hope to develop in this course.
  • Do not hesitate to ask appropriate questions in class or in office hours.
  • There is a big payoff to learning statistical programming. You will able to collect, enter, and manipulate data. You will be able to present descriptive statistics and demonstrate relationships between variables graphically. After STA512, you will be able to apply more advanced statistical techniques using SAS. Even if you do not become a statistician, these skills will be valuable in industry or research-oriented jobs. You will be able to be involved in more aspects of a research project. Moreover, the intuition that can be gained through learning statistical programming and intuition is an invaluable skill that can be applied to a wide variety of other jobs and applications.

Notes: Assignments and (especially exams) are subject to revision and re-scheduling.

All exam dates should be considered tentative.

Class Topics Assignments

Introduction / Class Overview

What is SAS?

Using the SAS Windowing Environment


Understanding SAS Data Libraries

Getting Information about a Dataset


Using SAS Online Help Documentation

Data Step Processing

Inputting Raw Data I

4 Inputting Raw Data II

SAS Datasets

Checking the Contents of a Dataset

5  DATA Step Processing  EXAM #1
6 Numeric Variables

Character Variables

Using SAS Functions

7  Handling Missing Data 

Acting on Selected Observations

Creating Subsets of Observations

Working With Grouped or Sorted Data

Using More than One Observation

 EXAM#2 distributed
9 Using Conditional Logic in SAS

Working With Dates

Methods of Combining Datasets

10 Merging Datasets

Modifying Datasets





Basic Statistical Procedures


13  EXAM #3

Graphics (cont'd)

SAS Macro Language

 EXAM #3
14 Output Delivery System (ODS)


Other advanced topics

FINAL EXAM distributed 
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