Download Syllabus: STAT 5814, Statistical Data Mining

Youngstown State University
Department of Mathematics and Statistics
Syllabus: STAT 5814, Statistical Data Mining, Spring 2016
Department Syllabus | Blackboard login Page
Instructor:
Office:
Phone No.:
E-mail:
Webpage:
Office hours:
Textbook:
Dr. Guang-Hwa Andy Chang
Room 623, Lincoln Building
(330) 941-1818
[email protected] or [email protected]
http://gchang.people.ysu.edu/
11:00 AM – noon and 1:15 PM – 2:00 PM, MW, and 12:00 PM – 1:00 PM TTh, or
by appointment
 SAS Programming 1: Essentials, Course Notes, by SAS Press, 2015.
 SAS Programming 2: Data Manipulation Techniques Course Notes, by SAS
Press, 2015.
 SAS Certification Prep Guide: Base Programming for SAS 9, by SAS Press. A
Sample Chapter / Ohiolink Ebook
 Applied Analytics Using SAS Enterprise Miner Course Notes, by SAS Press,
2015.
 The Elements of Statistical Learning, Data Mining, Inference, and Prediction,
by Hastie, Tibshirani, and Friedman, Publisher: Springer, 2009. [pdf]
 An Introduction to Statistical Learning with Applications in R, by James,
Witten, Hastie, and Tibshirani, Publisher: Springer, 2013. [pdf]
Additional reference: Cerrito, P. (2006), Introduction to Data Mining: Using SAS
Enterprise Miner, Ohiolink Ebook
Blackboard Course ID: STAT_5814_Chang: Statistical Data Mining
Grading Policy:
Quizzes and Assignments
Exam 1 (10%), Exam 2 (10%), Exam 3 (10%), Final (10%)
Total
Final Grade:
90% to 100%
80% to less than 90%
70% to less than 80%
60% to less than 70%
Below 60%
Course Assignments:
Textbook
Chapter
-A
- at least a B
- at least a C
- at least a D
- at most a D
Topics
60 %
40 %
100 %
1
1 - 12
Basic SAS Programming
2
1 - 12
Data Manipulation Techniques
3
1 - 22
SAS Base Programming Practice Problems
4
1-9
SAS Enterprise Miner
5
2, 3, 4, 9, 11, 13, 14
Data Mining Techniques
Additional notes from instructor
This course is designed to for students who are interested in statistical data mining and
statistical computing.
Students read and study materials provided from SAS Institute such as SAS programming, SAS
Enterprise Guide, and SAS Enterprise Miner to develop a variety of skills in statistical data mining.
Many of the concepts in this course require understanding of how the statistical methodologies
can be applied to data mining. Therefore, all concepts covered within the course are explored
with the use SAS, a powerful statistical analysis system that provides not only a great power for
statistical analysis but also tremendous data processing and report generating capability.
Make-up policy:
 Make-up tests will only be given to student who misses a test due to an extreme
emergency and has notified the instructor within 24 hours after the exam, or a sufficient
time period before the exam. The student will be expected to provide verification, such
as signed statement and phone number, to verify the reason for his or her absence from
the exam.
 No make-up quizzes will be given.
 Late homework or projects will not be accepted.
Homework and projects:
 Homework and projects will be assigned and be graded. "Study group" is strongly
encouraged. However, each student must hand in their own write-up. If you are having
trouble, please see me right away.
Attendance:
 It is expected that you will make every possible effort to attend all classes. In boarder
line situations, class attendance may affect a student grade.
 Although I feel that it is essential for you to attend class, no direct punishment will be
assessed to your grade if you choose not to attend class. However, in class activities that
count for grades will be given from time to time. If you missed classes it may affect your
grade. Students who missed class are responsible for finding out any pertinent
information concerning the course from the instructor.
 Some materials in the course may not be from the textbook. You are responsible for all
the materials covered in the course, take notes and download lecture notes if available.
Recommendations:

Students are responsible to read the course materials, assignments and deadlines, exam
schedule and other announcements. If you have questions, please contact instructor
right away.
 Successful students have found that the subject demands frequent intensive study with
lots of problem solving. Participating in group discussions is always helpful to yourself
and others in learning. If you have tried many times and still have difficulty solving a
problem, please feel free to see me.
 If you have any special problem or learning difficulties, please see me immediately.
Tentative schedule of tests:
Exam 1 (2/10)
Exam 2 (3/23)
Exam 3 (4/27)
Final Exam (5/2) 1:00 pm
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