Stats 202 Course Information

Tuesday, Thursday 9:00-10:15 AM in Terman 156

Professor David Mease

Email: dmease@stanford.edu


Phone: 419-944-9652


Office: 236 Sequoia Hall


Office Hours: Tuesday, Thursday 8:00-8:30 AM and by appointment


Telephone Office Hours for Remote Students: Tuesday, Thursday 7:30-8:00 AM and by appointment


TA Information:

Ya Xu (yax@stanford.edu), Office=237 Sequoia Hall

Ping Li (pingli98@stanford.edu), Office=229 Sequoia Hall

Click here for TA office hours.


Course Web Page: http://www.stats202.com


Textbook: Tan, Steinbach, Kumar, Introduction to Data Mining




Course Description: Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: decision trees, neural networks, association rules, clustering, case based methods, and data visualization. The following chapters from the textbook will be covered in this order:

Chapter 1 - Introduction
Chapter 2 - Data
Chapter 3 - Exploring Data
Chapter 6 - Association Analysis: Basic Concepts and Algorithms

Chapter 4 - Classification: Basic Concepts, Decision Trees, and Model Evaluation
Chapter 5 - Classification: Alternative Techniques
Chapter 8 - Cluster Analysis: Basic Concepts and Algorithms


Evaluation: Grades will be based on 3 components: 5 homework assignments (worth 40 points each), a single midterm exam (worth 100 points) and a comprehensive final exam (worth 200 points). The midterm exam date will be announced at least 3 class periods prior to the date. Special arrangements will be made for remote students who can not come to campus for the midterm or the final.


Grades: Grades will be assigned as follows:

95%-100% = A+
85%-95% = A
80%-85% = A-
77%-80% = B+
72%-77% = B
70%-72% = B-
67%-70% = C+
60%-67% = C
50%-60% = D
below 50% = F

Current point totals will be posted throughout the semester on the course web page.


Late Assignments/Make-Up Exams: I must receive prior notification and justification of your impending absence in order to authorize a make-up exam. Messages must be left either on my cell phone voice mail or sent by email prior to the start of the exam. An exam must be made up within one week of the original exam date. There will be no exceptions. Late homework assignments will have 5 points deducted for every day they are late.


Technology: A basic hand held calculator will be sufficient for the midterm and the final. To complete homework assignments you will need internet access, Microsoft Excel, and the R statistical software package (free download).


Academic Honesty: It is essential that you abide by the academic honesty policies of the university. In particular, you may not copy other students' work on exams or homework.